Key Responsibilities:

1. Data Pipeline Development:Design, build, and maintain scalable ETL/ELT pipelines to extract, transform, and load data from diverse sources.
   Automate data ingestion and processing workflows.
   
2. Data Architecture and Storage:Develop and optimize data models and databases (e.g., relational, NoSQL, or data lakes).
   Implement and manage cloud-based data storage solutions (e.g., AWS, Azure, Google Cloud).
   
3. Data Integration and Transformation:Integrate data from various structured and unstructured sources, including APIs and third-party systems.
   Ensure data quality, consistency, and accuracy through validation processes.
   
4. Performance and Scalability:Monitor, troubleshoot, and improve the performance of data systems and pipelines.
   Optimize storage and processing costs for large-scale datasets.
   
5. Collaboration and Support:Work closely with data scientists, analysts, and other stakeholders to understand their data needs.
   Provide technical guidance on best practices for data infrastructure.
   
6. Security and Compliance:Implement data governance, security protocols, and access controls.
   Ensure compliance with relevant data privacy regulations (e.g., GDPR, CCPA).
   

Qualifications:

1. Education and Experience:Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
   Proven experience in a data engineering role (2–5 years preferred).
   
2. Technical Skills:Proficiency in programming languages like Python, Scala, or Java.
   Experience with SQL and database management systems (e.g., MySQL, PostgreSQL).
   Hands-on experience with big data frameworks (e.g., Apache Spark, Hadoop).
   Familiarity with cloud platforms (AWS, Azure, GCP) and services like S3, Redshift, BigQuery, or Databricks.
   Knowledge of data integration tools (e.g., Apache Airflow, Kafka, or Glue).
   
3. Other Skills:Strong problem-solving and debugging abilities.
   Excellent communication and teamwork skills.
   Ability to manage multiple projects and deadlines.
   

Preferred Qualifications:

• Experience with machine learning pipelines and MLOps.
• Knowledge of containerization and orchestration (e.g., Docker, Kubernetes).
• Familiarity with CI/CD processes for data workflows.

We are seeking for an individual who is passionate about numbers, data and translating data into actionable insights that can drive decisions. Driven by curiosity and a desire to improve systems, you will be the data champion of Providend Holding Private Limited and its subsidiaries. You will develop data analytics strategies, manage the implementation of data analytics initiatives, while assisting with strategic decisions on data analytics platform. You will take responsibility in managing our databases, consolidating data from siloed systems into a centralized data platform, ensuring data integrity and developing reports.

On daily operational tasks, you will focus on the following areas:

1. Data Cleaning and Preparation: this includes filtering the data, handling missing values, and preparing the dataset for analysis to ensure accuracy and relevance.
2. Data Exploration and Analysis: use statistical tools and techniques to explore and analyse data, identifying patterns, relationships and trends.
3. Data Visualization: create visual representations of data findings through charts, graphs and dashboards to make the data understandable.
4. Reporting:prepare reports and presentations to communicate the insights and findings from the data to stakeholders, which can influence policy and decision-making processes.
5. Collaboration: work with other departments to understand their data needs and help them make informed decisions based on data insights.

To be successful in this position, you will be someone who is/has:

• Bachelor’s degree in data analytics
• Ability to work with stakeholders to assess business requirements and needs, and translate them into non-technical terms
• Ability to analyse existing tools and databases to provide data solution recommendations
• High-level experience in methodologies and processes for managing large-scale databases
• Demonstrated experience in handling large data sets and relational databases
• Working experience of Data ETL is a must
• Proficiency in process mapping tools, databases and ERP systems
• Hands-on knowledge in SQL and Python programming language is a must
• Experienced in handling huge data on Excel/CSV
• Good written and verbal communication skills
• Can-do attitude, good posture, problem solving mindset
• Initiative, drive and exceptional attention to details
• Tenacious and possesses a strong work ethic
• An independent worker, able to work without much guidance
• A strong team player
• Excellent organisational, problem-solving and multi-tasking skills

Desirable Skills:

• Data analytics services on AWS (e.g. Data Firehose, Kinesis, S3 Data Lake, Glue, QuickSight etc.) or Azure (e.g. Data Factory, Stream Analytics, Event Hubs etc.)
• Working experience in financial institutions is a plus

We are seeking a dynamic Data Analyst to be part of our mission to drive impactful decisions across our 22 markets. Working within our Analytics team, you'll support the team by providing high-quality insights, maintaining data consistency, and collaborating with internal teams to assist in decision-making. This is a foundational role offering the opportunity to grow technical skills, gain exposure to high-impact projects, and learn from experienced data professionals.

• Data Preparation & Analysis: Supporting data collection, cleansing, and preparation to ensure quality, reliability, and consistency. Conducting basic analyses using SQL and Excel, and assisting senior analysts with larger datasets.
• Dashboard Development: Creating and maintaining dashboards (e.g., in Looker or Tableau) for internal reporting needs. Ensuring they are user-friendly and meeting the requirements of key stakeholders.
• Reporting & Ad Hoc Analysis: Assisting in generating recurring reports and fulfilling ad-hoc analysis requests from internal stakeholders to support strategic decisions.
• Data Quality & Tracking: Monitoring data quality and participating in QA processes to ensure consistency across all reporting metrics.
• Collaboration: Working closely with senior analysts and team leads, learning from their approach to data modeling, visualization, and storytelling.
• Stakeholder Management: Partnering with business stakeholders across the organization to understand their analytical needs, proposing data solutions, and communicating insights in an actionable manner.

Data Scientist:

We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.

In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

Your goal will be to help our company analyze trends to make better decisions.

Responsibilities:

Identify valuable data sources and automate collection processes

Undertake preprocessing of structured and unstructured data

Analyze large amounts of information to discover trends and patterns

Build predictive models and machine-learning algorithms

Combine models through ensemble modeling

Present information using data visualization techniques

Propose solutions and strategies to business challenges

Collaborate with engineering and product development teams

Requirements and skills:

Proven experience as a Data Scientist or Data Analyst

Experience in data mining

Understanding of machine-learning and operations research

Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset

Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)

Analytical mind and business acumen

Strong math skills (e.g. statistics, algebra)

Problem-solving aptitude

Excellent communication and presentation skills

BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred

Are you driven by the desire to see your hard work directly impact others? Join the DNDTS team, where we excel in crafting success stories through dynamic projects. Each endeavor is a unique opportunity to contribute to our proven track record of achievements.

Experience the satisfaction of seeing your efforts transform into positive changes in people's lives. In our thriving SME environment, you won't be limited to a single role. You'll have the chance to engage in cross-departmental collaboration, fostering a rich learning experience.

As our team consistently grows, so do opportunities for career advancement. We embrace the startup culture by having a casual working attire and a flat hierachy across deparments. Your journey with us goes beyond a job—it's a chance to make a lasting impact while expanding your skill set. Join DNDTS and become a key player in our success story.

About the Company

Our company specializes in electronic products. We believe in the power of data to guide and refine our business strategies, including marketing, new business development, and overall operations. We are looking for a data analyst to help us unlock the potential of data and optimize our business for continued growth and success.

Roles & Responsibilities

As a Data Analyst, you will be responsible for gathering, analyzing, and leveraging data to inform decision-making and enhance our supply chain, sales channels, and overall business processes. You will collaborate with various departments to identify trends, improve efficiency, and maximize profitability.

Key Responsibilities

• Collect and analyze market data using our proprietary tool to uncover insights into consumer preferences, competitor strategies, industry trends, and potential opportunities for growth.

• Utilize our data analytics and visualization tools to examine data, communicate findings about key business aspects such as sales, revenue, costs, and production.

• Perform process analysis to pinpoint inefficiencies or bottlenecks and implement business process improvements for maximum profit.

• Conduct cost-benefit analyses to determine the optimal allocation of resources, investments in equipment, staffing decisions, or procurement strategies.

Qualifications / Requirements

• Bachelor's degree in Computer Science, Business Analytics, or a related field.

• Proficiency in common data analysis programming languages, libraries, and tools (e.g., Python, R, SQL, Pandas, NumPy).

• Solid data analysis and visualization skills, with experience in tools such as Tableau, Power BI, or similar platforms.

• Excellent communication skills, with proficiency in English.

• Ability to work independently and collaboratively with cross-functional teams.

• Strong problem-solving skills and a results-oriented mindset.

Benefits

• Flexible working hours

• Yearly Bonus

• Medical Insurance Coverage

• Staff Discounts

• Corporate Discounts at participating F&B and Retail Outlets

• Fast Career Advancement Opportunities

• Multi-Industry Exposure

• Working Location: East - Airline House - Next to Singapore Airlines HQ

Please ensure you meet the minimum qualifications before applying. We regret to inform that only shortlisted candidates will be notified. If you are a data analyst with a passion for using data to optimize operations and drive growth within the electronics industry, apply now to join our innovative company and embark on a rewarding career journey.

Be a part of our start-up where all decisions across BUs are data driven and never by gut.

CPO is a startup company dedicated to leveraging data-driven insights to drive innovation and growth. We are committed to harnessing the power of data to solve complex business challenges and deliver value to our customers. As we continue to expand our data analytics capabilities, we are seeking Data Scientists to join our team and contribute to our success.

As a Data Scientist, you will be at the forefront of our data analytics efforts, working closely with cross-functional teams to develop and deploy advanced analytical solutions. You will be responsible for analyzing large datasets, building predictive models, and generating actionable insights to inform business decisions. The ideal candidate will possess strong analytical skills, a deep understanding of statistical methods and machine learning techniques, and a passion for solving complex problems using data.

Key Responsibilities:

1. Collaborate with stakeholders to understand business objectives and identify opportunities for leveraging data analytics to drive business value.
2. Collect, clean, and preprocess large datasets from multiple sources to ensure data quality and integrity.
3. Apply statistical analysis and machine learning techniques to develop predictive models and algorithms for solving business problems.
4. Evaluate model performance and iteratively refine models to improve accuracy and effectiveness.
5. Generate actionable insights and recommendations based on data analysis, and present findings to stakeholders in a clear and compelling manner.
6. Work closely with engineering teams to deploy and operationalize analytical models in production environments.
7. Stay abreast of the latest developments in data science and machine learning, and proactively explore new techniques and methodologies to enhance analytical capabilities.
8. Collaborate with cross-functional teams to integrate data analytics into business processes and decision-making workflows.
9. Adhere to best practices in data governance, security, and compliance, ensuring the ethical and responsible use of data throughout the organization.

Qualifications:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field
• Experience with developing and deploying predictive models and algorithms would be a plus
• Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy) would also be a plus
• Strong understanding of statistical methods and machine learning techniques, including linear regression, logistic regression, decision trees, random forests, and neural networks.
• Experience working with big data technologies (e.g., Hadoop, Spark) and distributed computing frameworks.
• Solid understanding of data visualization techniques and tools (e.g., Matplotlib, Seaborn, Tableau).
• Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced, dynamic environment.
• Strong communication and presentation skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders.
• Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus.

We are a equal opportunity employer and is committed to diversity and inclusion in the workplace. We encourage individuals from all backgrounds to apply.

Job Overview:
We are seeking a skilled and motivated Data Scientist with expertise in Business and Systems Analysis to join our dynamic team. This role will focus on leveraging data to improve business processes, identify strategic opportunities, and optimize system performance within the Infocomm Technology sector.

As a Data Scientist in this role, you will collaborate closely with cross-functional teams to bridge the gap between technical data analysis and business strategy. You will use advanced data techniques, statistical methods, and business acumen to drive decisions and enhance system efficiencies.

Key Responsibilities:

• Analyze complex business processes and identify opportunities for process optimization through data-driven insights.
• Collaborate with stakeholders to define key performance indicators (KPIs) and business goals, translating them into actionable data-driven strategies.
• Develop models to assess and improve system performance, efficiency, and scalability within the Infocomm Technology environment.
• Conduct data analysis to derive actionable insights that influence business strategies, decision-making, and overall system architecture.
• Work with product and development teams to design, implement, and optimize analytics systems and tools that support business needs.
• Identify, analyze, and interpret trends or patterns in large data sets related to system performance, customer behavior, and market trends.
• Provide clear and compelling presentations of findings to both technical and non-technical stakeholders, ensuring alignment with business objectives.
• Actively participate in system design and improvement discussions, ensuring that data and business goals are aligned throughout the project lifecycle.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Programming & Systems Analysis, Science (Computer Science), or a related field.
• Proven experience in data analysis, business systems analysis, or data science within the Infocomm Technology sector.
• Strong understanding of business processes, system analysis, and how data analytics can enhance business performance.
• Proficiency in statistical and data modeling tools (Python, R, SQL, etc.) and business intelligence platforms (Tableau, Power BI, etc.).
• Experience with system design, requirements gathering, and data-driven solution implementation.
• Excellent communication skills with the ability to translate complex technical data into business terms for key stakeholders.
• Strong problem-solving skills and the ability to think strategically while applying analytical techniques.

Responsibility

The holder of the position is mainly responsible for the following areas in coordination with his / her superior:

Design and build the DWH database models (star schema).

Manage the semantic model in Oracle Analytics Cloud to provide a unified view of our organization's data.

Manage application roles and access rights for end users including row level security filters, to protect sensitive data.

Work with ETL specialists, IT business Consulting as well as external vendors to ensure data ingestion and integration into the database model

Collaborate with Business Controlling and business counterparts on new reporting requirements.

Ensure data quality, security and compliance with industry standards and internal guidelines.

Ensure proper documentation of data infrastructure, data models, workflows as well as security concepts in accordance with internal security policies.

Skills

Looking for a Data Engineer more focused on Database modelling, Currently in Oracle environment and going forward with GCP stack.

Proficiency in SQL and data warehousing

Strong understanding of data modelling techniques and hands on experience building database models (star schema).

Expertise with ETL (extract, transform, load) processes. Familiarity with BI tool integration such as Tableau or Looker

Strong analytical thinking, problem-solving capability, and ability to translate business needs into technical specifications.

Customer-oriented with good communication and interpersonal skills.

Responsibility

The holder of the position is mainly responsible for the following areas in coordination with his / her superior:

Design and build the DWH database models (star schema).

Manage the semantic model in Oracle Analytics Cloud to provide a unified view of our organization's data.

Manage application roles and access rights for end users including row level security filters, to protect sensitive data.

Work with ETL specialists, IT business Consulting as well as external vendors to ensure data ingestion and integration into the database model

Collaborate with Business Controlling and business counterparts on new reporting requirements.

Ensure data quality, security and compliance with industry standards and internal guidelines.

Ensure proper documentation of data infrastructure, data models, workflows as well as security concepts in accordance with internal security policies.

Skills

Looking for a Data Engineer more focused on Database modelling, Currently in Oracle environment and going forward with GCP stack.

Proficiency in SQL and data warehousing

Strong understanding of data modelling techniques and hands on experience building database models (star schema).

Expertise with ETL (extract, transform, load) processes. Familiarity with BI tool integration such as Tableau or Looker

Strong analytical thinking, problem-solving capability, and ability to translate business needs into technical specifications.

Customer-oriented with good communication and interpersonal skills.

Job Summary:

We are seeking a meticulous and driven Data Analyst to join our Contact Center team. This role involves analyzing data to support operational decision-making and drive process improvements within our contact center. The ideal candidate will be adept at extracting, cleaning, and interpreting data, with the goal of enhancing customer experience, efficiency, and overall performance.

Key Responsibilities:

• Extract, clean, and consolidate data from multiple sources to produce daily, weekly, and monthly reports.
• Write and optimize SQL queries for efficient data retrieval.
• Respond to ad-hoc data requests from projects and management, delivering timely and accurate insights.
• Collaborate with developers to automate reporting processes.
• Serve as a point of contact for project data-related inquiries.
• Analyze contact center performance metrics, including call volumes, response times, and customer satisfaction.
• Develop and maintain dashboards and reports to monitor key performance indicators (KPIs).
• Identify trends and patterns in data to guide strategic and operational decisions.
• Work with management and various departments to derive actionable insights and recommendations.
• Support the rollout of process improvements based on data insights.
• Ensure the accuracy and integrity of data across all reporting.
• Assist with demand forecasting and capacity planning using historical data trends.
• Stay informed about industry best practices and emerging technologies in data analysis.
• Perform other related duties as assigned by management.

Qualifications and Skills:

Education: Bachelor’s degree in Business, Computer Science, Mathematics, Data Analytics, or a related field.

Experience: 1–3 years of experience in data analysis, ideally in a contact center environment.

Technical Skills: Proficient in data analysis tools such as Excel, SQL, and Python. Experience with data visualization platforms, including Tableau, Power BI, or AWS QuickSight.

Communication: Strong written and verbal communication skills; able to effectively present insights and recommendations.

Problem Solving: Detail-oriented with strong analytical and critical-thinking skills.

Self-Motivation: Proactive and able to work independently with minimal supervision.

Time Management: Excellent organizational skills with the ability to manage multiple priorities and perform under pressure.

Quality Focus: High attention to detail, ensuring data accuracy and integrity.

Knowledge of Analytics: Familiarity with statistical analysis, modeling, and data visualization techniques.

" Programming skills in python

Training and deploying machine learning models end to end

Good understanding of basic statistics and deep learning techniques

Any experience in data integration, profiling,validation, and cleansing

Experience deploying TensorFlow and PyTorch into production.

• Good programming skills in Python
• Must possess experience or interest in training and deploying machine learning models end to end.
• Good understanding of basic statistics and deep learning techniques
• Prior experience in data integration, profiling, validation and cleansing
• Experience in Banking domain is mandatory
• Proficiency with SQL
• Software delivery
• Strong understanding of agile methodologies
• Strong understanding of CI/CD
• Strong understanding of test-driven development
• Comfortable using version control and enterprise task management tools.
  • Data Engineering
  • Experience in deploying TensorFlow and PyTorch into production
• Building data pipelines and architecture
• Should have extensive experience with relational and NO-SQL databases
• Should have proficiency in handling both structured and unstructured data sources
• Strong experience deploying applications to cloud platforms like Azure, AWS
• Interest in building efficient batch and streaming data engineering pipelines
• Exposure to distributed data processing platforms like Spark".

Responsibilities:

• Work closely with business (research analysts, quantitative strategist, end-users, etc.), data engineers, data scientists to implement and support data solutions that support common functions in the data lifecycle e.g. data onboarding, data distribution.
• Contribute, influence, and validate the design of lifecycle data solutions to ensure they meet both business and operational needs.
• Manage day-to-day operations for lifecycle data solutions such as collation of metadata, analysis of system operations data (e.g. data quality metrics, usage level of data distribution services).
• Perform data access control operations to ensure data ingested and distributed comply with enterprise data governance and data handling standards.
• Function as the Center of Excellence for the common data lifecycle services offered, defining standards and best practices, and designing process workflows to smoothen operationalization and to ensure compliance.
• Monitor, analyse, investigate, and resolve day-to-day operational incidents and provide advisory to users.
• Identify opportunities for continuous improvement in the assigned area of work.
• Manage and maintain strong stakeholder relationship to ensure continuous support and knowledge for existing and future data lifecycle needs.

Requirement:

• Possess a degree in Accounting, Finance, Engineering, Computer Science/Information Technology or related fields from recognized tertiary institution.
• At least 5 years of relevant experience in data management, data analytics, data engineering user. Preferably within investment and banking industry.
• Good understanding of the principles, key controls and processes relating to data management as well as data integration and data distribution.
• Good knowledge and experience in programming languages such as Python, Java, SQL etc.
• Familiar with data visualization tool (e.g. Tableau, PowerBI) and data virtualization technology such as Denodo is advantageous.
• Good at working with details and is meticulous for operations.
• Able to design and implement solution and perform code review.
• Excellent written and verbal communication skills.
• Strong interpersonal skill to interact with diverse stakeholders.
• Agile, fast learner and able to adapt to changes.
• Good team player, with strong analytical skill and enjoy complex problem solving
• Experience in the Systems Development Life Cycle implementation methodology (SDLC) and/or Agile methodologies like Scrum and Kanban.

Big Data Developer (3 – 10 Years)
§ Good understanding of concurrent software systems and building them in a way that is scalable, maintainable, and robust
§ Experience in designing application solutions in hadoop ecosystem
§ Deep understanding of the concepts in Hive, HDFS, yarn, Spark, Spark sql, Scala and Pyspark
§ HDFS file formats and their use cases (eg Parquet, ORC, Sequence etc)
§ Good knowledge in data warehousing system
§ Experienced in any scripting language (SHELL, PYTHON)
§ HortonWorks distribution and understanding on SQL engines (Tez, MR)
§ Java/RestServices/Maven experience is a value addition
§ Control-M development. Monitoring Resource utilization using Grafana Tool
§ Good skillset to create automation scripts in Jenkins & knowledge in working on automating builds, test frameworks, app configuration etc
§ Experience in implementing scalable applications with fully automated deployment and control using Bitbucket, Jenkins, ADO etc
§ Skillset:
o Mandatory: Big Data – Hive, HDFS, Spark, Scala, Pyspark.
o Good to have : Schedulers (Control-M), ETL Tool – Dataiku , Unix/Shell scripting , Knowledge of Integration services of FileIT/MQ and others , CI/CD tools – Jenkins, Jira, ADO Devops – tools suite , Oracle .

JD:

" Programming skills in python

Training and deploying machine learning models end to end

Good understanding of basic statistics and deep learning techniques

Any experience in data integration, profiling,validation, and cleansing

Experience deploying TensorFlow and PyTorch into production.

• Good programming skills in Python
• Must possess experience or interest in training and deploying machine learning models end to end.
• Good understanding of basic statistics and deep learning techniques
• Prior experience in data integration, profiling, validation and cleansing
• Experience in Banking domain is mandatory
• Proficiency with SQL
• Software delivery
• Strong understanding of agile methodologies
• Strong understanding of CI/CD
• Strong understanding of test-driven development
• Comfortable using version control and enterprise task management tools.
  • Data Engineering
  • Experience in deploying TensorFlow and PyTorch into production
• Building data pipelines and architecture
• Should have extensive experience with relational and NO-SQL databases
• Should have proficiency in handling both structured and unstructured data sources
• Strong experience deploying applications to cloud platforms like Azure, AWS
• Interest in building efficient batch and streaming data engineering pipelines
• Exposure to distributed data processing platforms like Spark".

JD:
Big Data Developer (3 – 10 Years)
§ Good understanding of concurrent software systems and building them in a way that is scalable, maintainable, and robust
§ Experience in designing application solutions in hadoop ecosystem
§ Deep understanding of the concepts in Hive, HDFS, yarn, Spark, Spark sql, Scala and Pyspark
§ HDFS file formats and their use cases (eg Parquet, ORC, Sequence etc)
§ Good knowledge in data warehousing system
§ Experienced in any scripting language (SHELL, PYTHON)
§ HortonWorks distribution and understanding on SQL engines (Tez, MR)
§ Java/RestServices/Maven experience is a value addition
§ Control-M development. Monitoring Resource utilization using Grafana Tool
§ Good skillset to create automation scripts in Jenkins & knowledge in working on automating builds, test frameworks, app configuration etc
§ Experience in implementing scalable applications with fully automated deployment and control using Bitbucket, Jenkins, ADO etc
§ Skillset:
o Mandatory: Big Data – Hive, HDFS, Spark, Scala, Pyspark.
o Good to have : Schedulers (Control-M), ETL Tool – Dataiku , Unix/Shell scripting , Knowledge of Integration services of FileIT/MQ and others , CI/CD tools – Jenkins, Jira, ADO Devops – tools suite , Oracle .

Job Summary:

We are seeking a skilled and motivated Data Engineer with expertise in Scala, SQL, and Hadoop to join our dynamic team. In this role, you will design, develop, and maintain scalable data pipelines and systems to process large datasets. You will collaborate with cross-functional teams to deliver high-quality solutions for data storage, transformation, and analytics.

Key Responsibilities:

1. Data Pipeline Development

· Design, build, and optimize scalable data pipelines using Scala and Hadoop frameworks.

· Implement ETL processes for ingesting, transforming, and storing data from various sources

2. Data Analysis and Query Optimization

· Write and optimize complex SQL queries for efficient data retrieval and transformation.

· Troubleshoot and resolve performance issues in queries and data workflows.

3. Big Data Ecosystem Management

· Manage Hadoop-based data infrastructure, including HDFS, Hive, and related components.

· Monitor system performance and optimize resource utilization in a distributed environment.

4. Collaboration and Problem Solving

· Work closely with data analysts, data scientists, and business stakeholders to understand requirements and translate them into technical solutions.

· Provide technical guidance and best practices for data engineering within the team.

5. Automation and Monitoring

· Develop scripts and tools to automate repetitive tasks and enhance system monitoring.

· Ensure data quality and consistency through validation and monitoring mechanisms.

6. Documentation and Compliance

· Document technical solutions, workflows, and processes to ensure knowledge sharing and reproducibility.

· Ensure compliance with data governance and security policies.

Skills and Qualifications:

Technical Skills:

· Proficiency in Scala programming and functional programming principles.

· Strong SQL skills, including query optimization and database design.

· Hands-on experience with Hadoop ecosystem tools such as HDFS, Hive, YARN, and MapReduce.

· Familiarity with other big data tools like Spark, Kafka, or Flink is a plus.

• Opportunity to shape and influence the future of data architecture
• 10% travelling required
• Benefit from mobility/relocation opportunities to other countries

about the company
My client is seeking a talented and adaptable Data Architect to join our team. This role will play a pivotal part in shaping and managing the data architecture for our global portfolio, supporting the company’s transformation journey as we migrate towards SAP and implement agile frameworks.

about the job
As a Data Architect, you will work closely with stakeholders across the globe, to design and implement robust data architecture frameworks. This role requires a dynamic individual with strong change management skills who can manage complex environments, juggle multiple projects, and drive business transformation through innovative data solutions.

• Develop data architecture frameworks for specific tech and data products in compliance with company’s global standards, including reference, meta, and master data management procedures.
• Continuously enhance these frameworks to meet evolving business needs while ensuring optimal data accuracy and accessibility.
• Translate complex business requirements into scalable data products, including databases, data warehouses, and data streams.
• Identify key data assets and assess the impact of product choices from a data architecture perspective.
• Ensure compliance of data models in new applications and align architecture decisions with global enterprise data strategies.
• Actively contribute to company’s agile transformation journey, driving the shift towards agile ways of working across multiple projects simultaneously.
• Manage and influence cross-functional teams to foster a culture of agility and adaptability in the organization.
• Coordinate with other Data and Tech Architects to ensure consistency in architecture decisions and alignment across products and markets.
• Participate in transversal initiatives, such as market intelligence and cross-product family projects, to drive enterprise-wide consistency and innovation.
• Advocate for global enterprise data strategies and provide best practices in data architecture to improve business outcomes.
• Bring forward innovative ideas and industry trends to enhance data usage and integration within the organization.

skills and experience required
At least 8 years of experience in data architecture or related fields, with proven expertise in designing and implementing data frameworks in complex environments.

Strong knowledge of agile methodologies, with experience managing change and transforming operational mindsets.

Hands-on experience in building data infrastructure and working with large financial or business datasets.

Broad knowledge of data integration, warehousing, and management tools, with expertise in SAP and BI platforms.

what's an offer
The permanent opportunity for a Data Architect will pay a salary range of $ 12,000 - $ 14,000 plus benefits. This opportunity provides a wider exposure to the inner workings of a global organization and the chance to make a meaningful impact on its overall success.

To apply online please use the 'apply' function, alternatively you can reach me at https://www.linkedin.com/in/Oliviatoh-032330132/. (EA: 94C3609 / R22109942)

Job Description:

• Design, develop, and optimize machine learning (ML) models and algorithms to address business challenges.
• Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models effectively.
• Train and fine-tune ML models using appropriate algorithms, techniques, and tools.
• Conduct evaluations to assess model performance, applying methods such as cross-validation, hyperparameter tuning, and ensemble learning.
• Work closely with software engineers and DevOps teams to deploy models in production environments.
• Implement APIs and integrate models into existing systems to enable real-time decision-making.
• Monitor deployed models to ensure optimal performance, address anomalies, and resolve issues.
• Continuously refine models and algorithms based on user feedback and performance metrics.
• Perform exploratory data analysis to uncover trends and insights.
• Use statistical methods and visualization techniques to communicate findings to stakeholders.
• Stay updated on advancements in ML and artificial intelligence (AI).
• Evaluate and recommend new tools, libraries, and methodologies to enhance workflows.

Job Requirements:

• At least 8+ years of hands-on experience in designing, developing, and deploying ML models for real-world applications.
• Deep Learning, Machine Learning, and Statistical Analysis
• Familiarity with Large Language Models and Generative AI technologies is a plus.
• Proficiency in Python and ML frameworks.
• Strong understanding of statistical analysis, probability theory, and hypothesis testing.
• Experience with cloud-based ML tools (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is advantageous.

Job Description

• Recommend and build require infrastructure for optimal extraction, transformation and loading of data from various sources such as ERP. MES and other systems using SQL technologies.
• Create, manage and maintain optimal data pipeline architecture. API and integration for ERP, MES and other systems used in the company.
• Monitor and manage database and related systems to ensure optimized performance.
• Assemble large, complex data sets that meet functional and non-functional business requirements.
• Working with stakeholders such as sales, finance, operations, design, and executive teams to support their data infrastructure needs while assisting with data-related technical issues.
• Build business intelligence and analytical tools using Power BI to utilize the data pipeline, and provide actionable insight into key business performance metrics.
• Participate in external and internal audit to ensure company data and related system is effective and validated.
• Create and maintain documentations and compliance for data and systems with reference to industry best practices.
• Perform other tasks as assigned by the supervisor.

Requirements

• Bachelor’s degree (or equivalent) in Computer Science, Information and Communications Technology, or related discipline
• 3 or more years with RDBMS and NoSQL databases
• 3 or more years of experience with Python, SQL, data visualization and exploration tools
• Working experience in MedTech / Manufacturing Industry
• Experienced in building and maintaining ETL processes.
• Experienced with Microsoft-based stack (M365, Power Platform, Azure, Dataverse,Microsoft SQL Server)
• Knowledge of best practices in ICT operations and data management
• Excellent problem solving and troubleshooting skills.
• Process orientated with great documentation practices.
• Communication skills, especially for translating technical concepts to non-technical business leaders.
• Ability to work on a dynamic, action-focused team that has concurrent projects

Job Description:

• Design, develop, and optimize machine learning (ML) models and algorithms to address business challenges.
• Collaborate with cross-functional teams to gather requirements, define objectives, and deploy models effectively.
• Train and fine-tune ML models using appropriate algorithms, techniques, and tools.
• Conduct evaluations to assess model performance, applying methods such as cross-validation, hyperparameter tuning, and ensemble learning.
• Work closely with software engineers and DevOps teams to deploy models in production environments.
• Implement APIs and integrate models into existing systems to enable real-time decision-making.
• Monitor deployed models to ensure optimal performance, address anomalies, and resolve issues.
• Continuously refine models and algorithms based on user feedback and performance metrics.
• Perform exploratory data analysis to uncover trends and insights.
• Use statistical methods and visualization techniques to communicate findings to stakeholders.
• Stay updated on advancements in ML and artificial intelligence (AI).
• Evaluate and recommend new tools, libraries, and methodologies to enhance workflows.

Job Requirements:

• At least 8+ years of hands-on experience in designing, developing, and deploying ML models for real-world applications.
• Deep Learning, Machine Learning, and Statistical Analysis
• Familiarity with Large Language Models and Generative AI technologies is a plus.
• Proficiency in Python and ML frameworks.
• Strong understanding of statistical analysis, probability theory, and hypothesis testing.
• Experience with cloud-based ML tools (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark) is advantageous.

Role & Responsibilities :

• Work closely with business (research analysts, quantitative strategist, end-users, etc.), data engineers, data scientists to implement and support data solutions that support common functions in the data lifecycle e.g. data onboarding, data distribution.
• Contribute, influence, and validate the design of lifecycle data solutions to ensure they meet both business and operational needs.
• Manage day-to-day operations for lifecycle data solutions such as collation of metadata, analysis of system operations data (e.g. data quality metrics, usage level of data distribution services).
• Perform data access control operations to ensure data ingested and distributed comply with enterprise data governance and data handling standards.
• Function as the Center of Excellence for the common data lifecycle services offered, defining standards and best practices, and designing process workflows to smoothen operationalization and to ensure compliance.
• Monitor, analyse, investigate, and resolve day-to-day operational incidents and provide advisory to users.
• Identify opportunities for continuous improvement in the assigned area of work.
• Manage and maintain strong stakeholder relationship to ensure continuous support and knowledge for existing and future data lifecycle needs.

Skillset Requirements

• At least 6 years of relevant experience in data management, data analytics, data engineering user. Preferably within investment and banking industry.
• Good understanding of the principles, key controls and processes relating to data management as well as data integration and data distribution.
• Good knowledge and experience in programming languages such as Python, Java, SQL etc.
• Familiar with data visualization tool (e.g. Tableau, PowerBI) and data virtualization technology such as Denodo is advantageous.
• Good at working with details and is meticulous for operations.
• Able to design and implement solution, and perform code review.
• Excellent written and verbal communication skills.
• Strong interpersonal skill to interact with diverse stakeholders.
• Agile, fast learner and able to adapt to changes.
• Good team player, with strong analytical skill and enjoy complex problem solving
• Experience in the Systems Development Life Cycle implementation methodology (SDLC) and/or Agile methodologies like Scrum and Kanban.

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About Sembcorp Industries

Sembcorp Industries (Sembcorp) is a leading energy and urban solutions provider, led by its purpose to drive energy transition.

Headquartered in Singapore, Sembcorp delivers sustainable solutions to support energy transition and urban development by leveraging its sector expertise and global track record.

For more information, please visit www.sembcorp.com.

PURPOSE AND SCOPE

The Data Analyst role is positioned to tap on the vast amounts of data available at Sembcorp Solar to better guide the organization in optimizing its operational and business processes. The role will reside within the Business Excellence Unit and will work on cross-functional projects.

KEY ROLES AND RESPONSIBILITIES

• Work with various departments within Sembcorp Solar to propose, develop and maintain automated data collection systems and pipelines across reporting lines.
• Provide stakeholders with accurate and relevant information through data-driven reports, visualizations, and presentations.
• Assist to identify and solve complex business problems by interpreting data trends and patterns.
• Develop statistical models and forecasts to support business planning.
• Continuously evaluate and refine existing data processes and methodologies to enhance data quality, integrity, and efficiency.

QUALIFICATIONS & EXPERIENCE

• Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, Engineering, Economics, or related fields.
• Demonstrable experience with data visualization tools like Tableau, Power BI, or matplotlib/seaborn in Python.
• Experience in data cleaning, transformation, and integration
• Experience working in cross-functional teams and collaborating with stakeholders from different departments.
• Proficiency in analyzing large datasets to extract meaningful insights.
• Knowledge of geospatial analysis and data-warehousing concepts can be advantageous.

SKILLS/COMPETENCIES & PREFERRED CHARACTERISTICS

• Understanding of statistical methods and concepts such as hypothesis testing, regression analysis, clustering, and classification techniques.
• Ability to use statistical methods and tools to interpret data and solve analytical problems.
• Ability to understand business requirements, translate them into analytical tasks, and provide actionable insights to stakeholders.
• Capability to identify problems and develop creative solutions using data-driven techniques.
• Effective communication of findings through reports, presentations, and visualizations to both technical and non-technical audiences.
• Thoroughness in data analysis and ensuring data quality and accuracy in findings and reports.
• Familiarity with specific industry trends and metrics relevant to the solar PV industry can be advantageous.

Fresh graduates are welcome to apply. Candidates will be expected to share about projects previously delivered.

At Sembcorp, our shared corporate behaviors underpin all the work that we do in building a sustainable future:

• Institution-first Mindset – Put the interest of the Group ahead of individual interests.
• Collaboration – Deliver through collaborating across markets, businesses and functions.
• Accountability – Hold team and self accountable to deliver on our commitments.

Big Data Developer (3 – 10 Years)
§ Good understanding of concurrent software systems and building them in a way that is scalable, maintainable, and robust
§ Experience in designing application solutions in hadoop ecosystem
§ Deep understanding of the concepts in Hive, HDFS, yarn, Spark, Spark sql, Scala and Pyspark
§ HDFS file formats and their use cases (eg Parquet, ORC, Sequence etc)
§ Good knowledge in data warehousing system
§ Experienced in any scripting language (SHELL, PYTHON)
§ HortonWorks distribution and understanding on SQL engines (Tez, MR)
§ Java/RestServices/Maven experience is a value addition
§ Control-M development. Monitoring Resource utilization using Grafana Tool
§ Good skillset to create automation scripts in Jenkins & knowledge in working on automating builds, test frameworks, app configuration etc
§ Experience in implementing scalable applications with fully automated deployment and control using Bitbucket, Jenkins, ADO etc
§ Skillset:
o Mandatory: Big Data – Hive, HDFS, Spark, Scala, Pyspark.
o Good to have : Schedulers (Control-M), ETL Tool – Dataiku , Unix/Shell scripting , Knowledge of Integration services of FileIT/MQ and others , CI/CD tools – Jenkins, Jira, ADO Devops – tools suite , Oracle .

Helmut Schroeder is a pioneering intellectual property (IP) management company dedicated to acquiring, managing, and maximizing the value of our rights portfolio. We use data-driven insights and innovative strategies to uncover opportunities in the IP market, enabling artists and investors to thrive in the ever-evolving creative industry.

We are seeking a skilled and passionate Data Scientist to join our team. This role will play a crucial part in driving data-informed decision-making in an exciting and dynamic domain.

Key Responsibilities

As a Data Scientist, you will:

• Develop and implement models to analyze the financial performance and future potential of IP assets.
• Use machine learning and statistical techniques to predict trends in IP valuation.
• Integrate and clean data from diverse sources, including streaming platforms, social media, financial reports, and licensing agreements.
• Collaborate with cross-functional teams, including investment analysts, legal experts, and software developers, to design and deploy analytics solutions.
• Build dashboards and visualization tools to communicate insights effectively to stakeholders.
• Identify market patterns and trends to inform strategic decisions around acquisitions and portfolio management.
• Stay current with the latest developments in data science and the creative industry to bring innovative solutions to the company.

Qualifications

Technical Skills:

• Programming Languages: Proficiency in Python for data analysis and modeling.
• Data Manipulation: Experience with DynamoDB/SQL and working with large, complex datasets.
• Machine Learning: Familiarity with libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
• Statistical Analysis: Strong foundation in statistical modeling, hypothesis testing, and predictive analytics.
• Big Data: Familiarity with distributed data systems like Hadoop, Spark, or cloud-based data warehouses (e.g., BigQuery, Snowflake).

General Requirements:

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field. A Master's/PhD is a plus.
• 2+ years of experience in data science, preferably in media or financial domains.
• Strong problem-solving skills and ability to translate business needs into technical solutions.
• Excellent communication skills, with the ability to present complex findings in a clear and actionable manner.

Why Join Us?

• Work at the intersection of art, law, data, and investment, shaping the future of Singapore's IP landscape.
• Collaborate with a team of experts passionate about data and innovation.
• Flexible working environment with remote work options.
• Competitive salary and benefits, including opportunities for professional development.
• Make an impact by supporting artists and maximizing the value of their creative work.

The Data Analyst will be responsible for designing, developing, and implementing methods, processes, and systems to consolidate, cleanse, and analyze diverse and unstructured data sources. The role will focus on leveraging advanced data analytics, machine learning, and statistical techniques to derive actionable insights and support decision-making at the management level.

Responsibilities:-

• Design, develop and program methods, processes, and systems to consolidated and analyse unstructured, diverse data sources to generate actionable insights and solutions for Management
• Develop and code software program, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources.
• Assist to automate repetitive data tasks, to streamline the process, and minimize manual intervention.
• Assist to create data visualization for the business.

Requirements:-

• Minimum Degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• Minimum 1-2 years of experience in a Data Analyst
• Minimum 1-2 year of working experience in similar industry would be a plus.
• Proficiency in programming languages such as Python, R, SQL & PowerShell, with experience in data manipulation and analysis libraries.
• Experience with data visualization tools (eg: PowerBI).
• Strong in Microsoft