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

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".

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.

· Proven experience as a Data Engineer, with a strong focus on AWS Redshift.

· Expertise in data modeling techniques and best practices.

· Experience with ETL tools and processes.

· Familiarity with data warehousing concepts and tools.

· Proficient in SQL and scripting languages such as Python or Java.

· Experience with other AWS services such as S3, Lambda, and Glue.

· Strong problem-solving skills and attention to detail.

· Excellent communication and collaboration skills to work effectively with team members and stakeholders.

· Certifications in AWS or data engineering (e.g., AWS Certified Big Data, AWS Certified Data Analytics) are a plus.

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

• 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.

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.

* He must be having good Business understanding of data model designing (Conceptual Data Model, Logical Data Model , Physical Data Model) of new aged digital implementations based on Microservices and Be Spoke Application.

* He must be versed with agile implementation of Data modeling.

* He must have working exp in implementation IT Project as Data Architect .

* He must be able to collaborate with IT teams, analyze business needs, and ensure data solutions align with Project phase goals.

* Responsibilities include data modeling, defining database architecture, optimizing data retrieval, and ensuring data security.

* Strong knowledge of AWS Postgres database technologies, data warehousing, Data security and data governance is essential for this role. Also Good to have working exp as Data Architect in SG Gov Sector in IT Project.

Responsibilities:

1. Develop and implement data mining strategies to extract meaningful insights from large datasets, utilizing statistical methods and machine learning algorithms.
2. Conduct data cleaning, preprocessing, and transformation to ensure high data quality and integrity for analysis.
3. Create interactive dashboards and comprehensive reports using Power BI to effectively communicate findings to stakeholders.
4. Use visual storytelling techniques to present analytical results in a clear and engaging manner.
5. Work closely with various teams to understand their data requirements and provide tailored analytical support.
6. Monitor the performance of models and iterate on improvements based on stakeholder feedback and new data insights.
7. Prepare detailed reports summarizing analysis results for management review, ensuring actionable recommendations are included.

Qualifications:

1. Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field; Master’s degree preferred.
2. Minimum of 3 years of proven experience in data mining, statistical analysis, or a related field.
3. Proficient in Power BI or similar data visualization tools.
4. Excellent problem-solving skills, with the ability to work both independently and collaboratively.
5. Strong communication skills to clearly convey complex information to diverse audiences

Working Hour

• Monday to Friday | 9am to 6pm

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.
• Partner with business experts to enrich the data and find meaningful insights that can be applied to build actionable solutions.
• Automate repetitive data tasks, to streamline the process, and minimize manual intervention.
• Create data visualization to effectively communicate findings and recommendations to stakeholders.
• Stay update on industry trends and best practices in data science, machine learning, and artificial intelligence.
• Support Global IFF Business Control on any tasks or projects handling requirements.
• Provide support in administrative matters and ad-hoc tasks assigned by HOD from time to time.

Requirements:-

• Minimum diploma in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• Minimum 1-2 years of experience in a data science role.
• Minimum 1-2 year of working experience in similar industry would be a plus.
• Proficiency in programming languages such as Phython, R, SQL & PowerShell, with experience in data manipulation and analysis libraries.
• Experience with data visualization tools (eg: PowerBI) and proficiency in communicating complex analysis results to non-technical stakeholders.
• Strong problem-solving skills and analytical thinking, with the ability to translate business questions into data-driven solutions.
• Strong in Microsoft

Responsibilities

• Data Collection & Reporting: Assist in gathering, organizing and analyz-ing data from web based data, focusing on key performance indicators such as waste and recycling tonnage.
• Liaising with operations: Work closely with operational teams ensure timely and accurate submission of operations data. Provide support and guidance to operations as needed to improve data reporting processes.
• Data Accuracy & Quality Assurance: Perform regular data quality checks to verify accuracy, completeness, and consistency of sustainability data. Identify discrepancies or issues and work with local teams to resolve them.
• Updating of route plan masterlist: Assist in the updating process for new collection data points.
• Liaising with estate managers: Provide estate managers sustainability data in a timely and accurate manner.
• Data Entry & Updates: Ensure that all sustainability data is entered into the relevant tracking systems on time and in line with reporting sched-ules.
• Develop & Maintain Reporting Tools: Assist in creating and maintaining data dashboards and reports that provide real-time insights into sustaina-bility performance.
• Reporting Support: Help prepare periodic sustainability reports and presentations for internal stakeholders
• Collaboration & Communication: Work closely with customer service team to serve as a joint point of contact for sustainability data
• Ad-hoc Project Support: Assist with various sustainability initiatives and projects as required, providing data support and helping to implement new programs or processes

Requirements:

• Have at least 1-2 years of experience in sustainability data or related fields.
• Graduated from a diploma program in Environmental Science, Sustaina-bility, Engineering, Business, or a related field.
• Strong analytical skills, with experience in data collection, cleaning, and analysis.
• Proficiency in Microsoft Excel, Google Sheets. Data analysis tools (e.g., Power BI, Python) is a plus but not required.
• Interest in sustainability and environmental impact, with a willingness to learn and contribute to global sustainability efforts

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.

Overview

Each year, we as Oldendorff, carry about 380 million tons of bulk and unitized cargo around the world. We perform 15,000 port calls in 118 countries. On average, we operate 700 chartered and owned ships at any one time. Being with us, means working in a continuously changing internationally environment, where reliability is appreciated as is team spirit. Combined with a healthy driver to keep seeking for areas to develop you and your company to reach higher goals – we welcome you to set sail with us.

After the strategic shift towards a cloud-based and innovative Technology organization, we established a dynamic, modern and agile working environment. Join our culturally diverse 80 people-strong team, encouraging creativity and shaping Oldendorff’s digital future.

Our data engineering team designs, builds, and maintains scalable data pipelines and architectures to ensure seamless data flow and accessibility across the organization. The team works collaboratively with data scientists, analysts, and other stakeholders to optimize data integration, storage, and retrieval processes.

Essential Functions:

· In a group effort together with your team, you are shaping and designing our BI and data-architecture solution in the Cloud.

· You are developing data solutions with several platform technologies (e.g. Databricks, Logic Apps, Azure Data Factory, Azure Synapse).

· You are developing low-code solutions with Power Platform.

· You have comprehensive knowledge of DevOps principles.

· You are working on the development of our integrated data layer as the foundation of implementing data-driven analysis and reports using SQL and PySpark.

· You are supporting our development team in their selection and implementation of suitable data technologies.

· You are examining and evaluating new developments in the field of data technologies.

Skill Requirements:

· Successfully completed training or studies in the field of IT

· You have worked with databases or BI environments for more than 3 years, ETL/ELT experience with data integration and data processing.

· You are already experienced in working with different types of database technologies, scalable big data storage, preferable Azure Data Lake Storage.

· You are experienced in working with cloud technologies and cloud-based data-integration tools.

· Further to that, you are ideally familiar with agile project-processes (i.e. Scrum, Kanban) and you bring along some knowledge in Atlassian Suite (i.e. Jira, Confluence, Bitbucket and Bamboo).

· You are solution-driven, proactive and a team player.

· You enjoy communicating with our colleagues in English, because our team is indeed very international.

Mandatory Skills

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

Data Pipeline Development

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

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

Data Analysis and Query Optimization

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

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

Big Data Ecosystem Management

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

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

Collaboration and Problem Solving

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

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

Automation and Monitoring

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

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

Documentation and Compliance

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

o Ensure compliance with data governance and security policies.

Skills and Qualifications

Technical Skills:

o Proficiency in Scala programming and functional programming principles.

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

o Hands-on experience with Hadoop ecosystem tools (HDFS, Hive, YARN, MapReduce).

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

Problem-Solving:

o Strong analytical skills with the ability to troubleshoot and resolve complex data issues.

Communication:

o Excellent communication skills to effectively collaborate with technical and non-technical stakeholders.

Experience:

6+ years of experience in data engineering, big data technologies, or a

similar role.

Job Title: Data Scientist / ML Engineer Intern

Job Description

We are seeking interns to support our AI/ML Product Development and Solution Delivery on a short-term basis (3-6 months). Ideal candidates would be students from tertiary institutions with a keen interest in AI/ML.

Key projects needing assistance are stated below and key tasks include:
· Accelerating development on ongoing projects.

1. Smart Retail Platform (with Gen AI Agent)
2. Vision analytics as-a Service

· Providing support for day-to-day tasks.

Key Responsibilities include:
- Acquire knowledge and understanding of telco data and its analytics use cases.
- Design, develop, and maintain backend systems for handling and processing large volumes of data.
- Implement scalable data pipelines for ingesting, transforming, and storing data from diverse sources.
- Create prototypes for proof-of-concept (POC) applications and develop user interfaces for showcasing big data insight.

- Assist in building and optimizing video analytics algorithm.

- Explore and implement multimodal models for real world applications.

- Gain hands-on experience with computer vision and multimodal AI packages.
- Develop proficiency in open source packages and NVIDIA frameworks, including but not limited to: YOLO, VILA, NIMS, NEMO.

Qualifications

• Product thinking mindset.
• You are a coder.
• You like the opportunity to directly shape our new AI products from the first day.
• You are passionate about MLOps and love building auto-scaling ML systems.
• You like to take initiative to improve existing state of data science pipelines and passionate to embrace new changes.

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.

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.

Responsibilities

• Designing enterprise-grade Power BI solutions and analytical data modeling.
• Managing and delivering Power BI projects within timelines.
• Developing Power BI standards, guidelines, and best practices.
• Working with data engineers, data scientists, and other stakeholders in the implementation of Power BI dashboards and reports.
• Leading and providing technical support for Power BI dashboards.
• Organizing and holding workshops and clinics to help HPB employees become more adept in Power BI.

Requirements

• Minimum years of experience in end-to-end Power BI dashboard solutions/data visualization design, adopting good practices that encourage efficient data usage, scalability, extensibility, and reusability.
• Relevant work experience in data integration, analytics, data extraction, transformation and load (ETL), basic exploratory data analytics (EDA), data cleaning, and/or feature engineering.
• Experience in data science is an added advantage.
• Strong skills in analytical data modeling and analysis concepts are an added advantage.
• Experience within healthcare industry
• Technically competent in Microsoft BI and DAX (Data Analysis Expressions) scripting.
• Proficient in SQL (Structured Query Language).
• The following experience and knowledge would be advantageous:
  • Proficiency in Microsoft Azure.
  • Experience with PySpark.