Responsibilities:

• Responsible for design and optimizing of complex SQL queries to generate reports from the data platform.
• Ensure the accuracy, security and reliability of data used in generated reports. Making sure that the data follows local regulations and company policies.
• Support the creation of data visualization tools and dashboards, ensuring they are built on robust and reliable structures within the company's data platform.
• Collaborate with Data Engineers, Data Scientists, and Data Management teams.
• Liaise with business departments to understand their reporting requirements.
• Conduct in-depth analyses to identify trends, patterns and actionable insights.
• Identify automation opportunities and manage departmental automation processes.
• Improve data collection models and ensure the performance of datasets.
• Develop and maintain documentation including data dictionaries and report definitions.
• Carry out any additional tasks assigned by the Supervisor.

Requirements:

• Degree in Statistics, Engineering, Computer Science or equivalent.
• At least 2 years of relevant work experience.
• Knowledge of SQL and programming.
• Experience using Python and PowerApps is an added advantage.

Interested applicants are welcome to submit your resume to [email protected]

EA. R1107675

Agency no. 07C3676

We are looking for a highly skilled Data Engineer to join our team and help build scalable data pipelines and systems. The ideal candidate will have experience in designing, implementing, and optimizing data architectures to enable effective data-driven decision-making. This role involves working with large datasets, building ETL pipelines, integrating data from various sources, and collaborating with cross-functional teams to ensure seamless data operations.

Key Responsibilities:

1. Data Pipeline DevelopmentDesign, build, and maintain scalable and efficient ETL/ELT pipelines to extract, transform, and load data from diverse data sources into data warehouses or data lakes.
   Ensure data pipelines are robust, reliable, and optimized for performance.
   
2. Data Integration & StorageIntegrate structured and unstructured data from various internal and external sources.
   Develop and maintain data storage solutions, including data lakes, data warehouses, and databases.
   Work with both relational databases (SQL Server, PostgreSQL, MySQL) and NoSQL databases (MongoDB, Cassandra, DynamoDB).
   
3. Data Modeling & ArchitectureDesign and implement data models to support analytical and reporting needs.
   Collaborate with data scientists, analysts, and stakeholders to understand data requirements and translate them into scalable solutions.
   Implement best practices in data governance, data quality, and metadata management.
   
4. Data Pipeline Monitoring & OptimizationMonitor and troubleshoot data pipelines to ensure data availability, accuracy, and integrity.
   Optimize existing data systems for performance, scalability, and cost-efficiency.
   Implement error-handling mechanisms and recovery strategies for critical pipelines.
   
5. Collaboration & DocumentationCollaborate with software engineers, DevOps teams, and business stakeholders to support data-related technical issues and infrastructure requirements.
   Document data processes, pipeline configurations, and system designs to maintain a clear understanding of the data ecosystem.
   

Required Skills:

• Programming: Proficiency in Python, Java, or Scala for data pipeline development.
• Data Technologies: Experience with Apache Spark, Hadoop, Kafka, and Flink.
• ETL Tools: Experience with ETL tools like Apache Airflow, Informatica, or Talend.
• Databases: Strong SQL skills and experience with relational databases (PostgreSQL, MySQL, SQL Server) and NoSQL databases (MongoDB, Cassandra).
• Cloud Platforms: Hands-on experience with cloud platforms like AWS (Redshift, S3, Glue), Azure (Data Lake, Synapse), or Google Cloud (BigQuery, Dataflow).
• Data Warehousing: Strong understanding of data warehousing concepts, including dimensional modeling, star/snowflake schema, and data marts.
• Version Control: Proficiency in using Git for source control and versioning.
• Big Data: Experience in working with large datasets and distributed computing frameworks.

Preferred Qualifications:

• Certification in AWS, Azure, or Google Cloud related to data engineering.
• Experience in data streaming technologies like Apache Kafka, AWS Kinesis, or Azure Event Hub.
• Familiarity with DevOps practices and CI/CD pipelines for data infrastructure.
• Knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Strong analytical and problem-solving skills with a keen attention to detail.
• Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Educational Qualification:

• Bachelor’s degree in Computer Science, Data Science, Information Technology, or a related field.

Our Client:

• Engineering Industry
• Central Region
• 5 Days, Monday to Friday
• Up to $10,000 per month

Responsibilities:

• Design and build data pipelines infrastructure to collect, process and store data from various sources.
• Develop data assets platform to provide a centralized repository for managing and accessing data assets.
• Implement automated SQL queries based on user-defined criteria or business requirements.
• Use techniques like query templates, metadata-driven generation, or machine learning algorithms to generate SQL queries.
• Create new IPs in Singapore in area of expertise.
• Manage collaboration projects with Institute of Higher Learning or Research Institutes on new technology development.

Requirements:

• Degree / Masters / PhD in Computer Science, Data Science, Statistics Applied Sciences or related field.
• Proficiency in Python, SQL, Java or Scala programming languages.
• Understand data warehousing concepts, ETL (Extract, Transform, Load) processes and tools like Informatica, Talend, or Airflow.
• Knowledge of relational databases (MySQL, PostgreSQL, Oracle) and NoSQL databases (MongoDB, Cassandra).
• Familiar with Apache Airflow, Kubernetes or Ansible for automating data pipelines and infrastructure.

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JTE Recruit Pte Ltd | EA Lic No: 14C7215

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

Requirements and Skills: Data Architect

• A bachelor's degree in computer science, information technology, or a closely related discipline is usually necessary. A master's degree is preferable
• Developed comprehensive architectural plans to meet specific budgetary requirements and project timelines
• Understanding the Enterprise Wide Data-Warehouse developed using FSLDM Model, the databases, technicality in loading & retrieving data.
• Produced monthly & Weekly reports through Automation using ETL,Datan Wrangling & BI tools using Enterprise wide DW.
• Utilized data visualization tools to effectively communicate business insights.
• Identified, analyzed and interpreted trends or patterns in complex data.
• Formulate and maintain Data Governance, framework for Data Ingestion, Data Quality tracking, Meta Data Management, Classifiers and Security across Platform layers and application based on sensitivity of data being stored including Data Lake, EDW and Business Intelligence.
• Designed internal process improvements to automate repetitive tasks,shortening data delivery times
• Core-banking Solution to enhance payment processing using Application programming, Containers & APIs.
• Work with Java & front end developers and support back end processing through API's for Domestic & International Payments.
• Design an enterprise wide Warehouse system using FSLDM and Source Core Banking data for Analytics and Regulatory reporting.

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:

Key Responsibilities:

• Support day-to-day Business-As-Usual (BAU) operations and data engineering activities for the Enterprise Data Warehouse.
• Design, develop, and maintain scalable data solutions for data storage, transformation, and analytics.
• Collaborate with cross-functional teams to ensure seamless data integration and operational efficiency.
• Troubleshoot and resolve technical issues to maintain system performance and reliability.
• Ensure adherence to best practices and standards for data engineering solutions.

Qualifications and Skills:

• A degree in Computer Science, Information Technology, or a related field.
• Strong hands-on experience in:Oracle PL/SQL
  Informatica PowerCenter
  
• Proficiency in SQL across any Relational Database Management System (RDBMS).
• Experience with Systems Development Life Cycle (SDLC) implementation methodologies and/or Agile frameworks (e.g., Scrum, Kanban).
• Ability to learn quickly, adapt to changing requirements, and work in an agile, fast-paced environment.
• Strong analytical and problem-solving skills with a passion for solving complex issues.
• Excellent teamwork and communication skills to collaborate effectively with technical and non-technical stakeholders.
• Experience with dbt Core or Snowflake is a plus.

The successful candidate will play a critical role in supporting the smooth operation of the Enterprise Data Warehouse while ensuring high-quality data engineering solutions and seamless integration across teams.

· 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 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.

Requirements:

· Proficient in Python, SQL, PL/SQL, and CICD.

· Familiarity with data warehouses such as Snowflake and Oracle.

· Strong analytical and problem-solving skills.

· Good team player and communication skill.

Skillset (Good to have)

· Familiarity with Denodo

Please refer to U3’s Privacy Notice for Job Applicants/Seekers at https://u3infotech.com/privacy-notice-job-applicants/. When you apply, you voluntarily consent to the collection, use and disclosure of your personal data for recruitment/employment and related purposes.

* 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

Are you ready to dive into the exciting world of hedge funds? We’re on the hunt for a talented and driven Data Engineer with 3-4 years of experience to become a vital part of our client's team.

In this role, you’ll be the mastermind behind designing, building, and fine-tuning data pipelines and infrastructure that power our cutting-edge quantitative and investment strategies. Think of it as being the architect of our data universe, where every piece you build has a direct impact on high-stakes decision-making.

Key Responsibilities:

1. Data Pipeline Development: Design, develop, and maintain robust and scalable data pipelines to ingest, clean, and transform large volumes of structured and unstructured data from multiple sources.
   Ensure data availability, reliability, and consistency for downstream analytics and modeling.
   
2. Data Integration and Storage: Implement efficient data integration solutions to connect various internal and external data sources.
   Build and optimize data storage systems, including data lakes, warehouses, and real-time streaming platforms.
   
3. Performance Optimization: Monitor and improve the performance of ETL processes and database systems to minimize latency and maximize throughput.
   Ensure high availability and fault tolerance of data infrastructure.
   
4. Collaboration with Teams: Work closely with quantitative analysts, portfolio managers, and data scientists to understand their data requirements and provide tailored solutions.
   Collaborate with IT and DevOps teams to deploy and maintain infrastructure in production environments.
   
5. Data Quality and Governance: Establish and enforce data quality and validation processes to ensure accuracy and completeness.
   Implement data governance practices to maintain compliance with regulatory requirements.
   
6. Technology Exploration: Stay updated with the latest advancements in data engineering technologies and tools.
   Evaluate and recommend new technologies to enhance the fund's data capabilities.
   

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Experience: 3-4 years of hands-on experience in data engineering, preferably in the financial services or hedge fund industry.

Technical Skills:

• Proficient in programming languages such as Python, Java, or Scala.
• Strong experience with SQL and database technologies (e.g., PostgreSQL, MySQL, or Snowflake).
• Hands-on experience with big data tools (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP).
• Experience with data pipeline tools such as Apache Airflow, Luigi, or similar frameworks.
• Familiarity with real-time streaming technologies like Kafka or Kinesis.
• Understanding of data modeling, warehousing concepts, and ETL best practices.

Preferred Qualifications:

• Experience in the hedge fund or financial services industry is highly desirable.
• Knowledge of financial datasets and market data providers (e.g., Bloomberg, Refinitiv).
• Familiarity with machine learning workflows and integrating AI/ML models into data pipelines.

If you or anyone within your network is keen to explore the opportunity then do share your resume with [email protected]

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.

Key Responsibilities:

• Data Infrastructure Development: Design and build scalable, efficient, and secure data infrastructure to support advanced analytics and reporting systems.
• ETL Pipeline Development: Develop and maintain robust ETL (Extract, Transform, Load) pipelines to process data from various sources, ensuring high-quality, consistent, and accurate data.
• Data Integration: Integrate multiple internal and external data sources, ensuring seamless data flow across platforms.
• Data Modeling: Create and maintain data models and schemas that ensure the efficient storage and retrieval of data.
• Optimization and Performance Tuning: Enhance the performance and scalability of data pipelines, optimizing for speed and reliability.
• Collaboration: Work closely with data scientists, business analysts, and other teams to ensure that data is organized and accessible for analysis, reporting, and machine learning applications.
• Data Governance: Implement data quality control processes to maintain data integrity and consistency.
• Automation: Automate data workflows and systems to ensure efficiency and reduce manual work.
• Troubleshooting and Maintenance: Monitor the health of data systems, diagnose issues, and maintain optimal data system performance.

Qualifications:

• Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent professional experience).
• Experience:2+ years of experience in data engineering, database management, or a similar field.
  Experience working with cloud platforms (AWS, Google Cloud, or Azure).
  Proficiency in relational and NoSQL databases (MySQL, PostgreSQL, MongoDB, Cassandra).
  Solid experience with ETL processes and tools (e.g., Apache Airflow, Talend, or custom-built pipelines).
  Familiarity with data warehousing solutions such as Snowflake, Redshift, or BigQuery.
  
• Technical Skills:Strong proficiency in programming languages such as Python, Java, or Scala.
  Expertise in SQL for data querying, optimization, and performance tuning.
  Experience with data processing frameworks like Apache Spark or Hadoop.
  Version control experience with tools like Git.
  

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.

Responsibilities

• Perform operation, installation, and monitoring of big data platforms
• Ensure the reliability and normal operation of multiple core systems for big data and online computing, resolving issues within the agreed SLA
• Evaluate infrastructure requirements for deployments and upgrade activities
• Develop and maintain technical documentations related to design, configuration, troubleshooting, backup, DR, etc
• Ensures deployment and operations of the data platform comply with prevailing security, regulations and audit requirements
• Provide recommendations on data governance practices and in-depth optimizations best practices

Requirements
• primary skillset: DevOps and system engineers in Unix
• Solid computer software basic knowledge; understand Linux operating system, storage, network IO and other related principles
• Familiar with one or more programming languages, such as Python/Go/Java/Shell/Ansible
• Experience with Cloudera, Informatica, or Denodo and its runtime components would be highly advantageous
• Relevant computing/distributed/big data system experience (Hadoop/HDFS/Kubernetes/Docker/OpenStack/Hadoop/Spark/Flin etc.)
• Good data structure and system design skills
• Good knowledge of information security

Next Step

• Prepare your updated resume and expected package.
• Simply click on 'Apply here' or email to [email protected] to drop your resume
• All shortlisted candidates will be contacted.

Tamanna Bilandi

EA Licence No. 91C2918

Personnel Registration No. R2096241

Responsibilities

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

• Develop and implement techniques and analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualisation software.

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

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

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

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

Skills/Requirement

• Proficiency in Scala programming and functional programming principles.

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

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

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

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

• 6+ years of experience in data engineering, big data technologies, or a similar role.

Company’s Profile:

Our client is an international technology and engineering company that specialises in providing innovative digital and security solutions to their esteemed clients. They are well-known for their dedication of quality delivery standards with more than 15,000 engineers globally supporting projects. They have an international presence in over 100 countries worldwide and are looking out for AI Engineers to join their team and contribute to their ongoing success.

Location: Ang Mo Kio/Yio Chu Kang area

Job Responsibilities:

• Work with internal & external stakeholders on data-related technical issues and support their data infrastructure needs
• Work closely with data scientists to solicit data requirements to support modeling works
• Design, develop, document, manage and maintain data models, ETL processes, data warehouse, data management and pipeline solutions for large volume of structured/unstructured data from disparate sources and with different latencies (e.g. on-demand, batch, real-time, near-real-time)
• Define, monitor and report SLAs for data pipelines and data products
• Understand data security and governance standards or requirements to implement solutions that ensure adherence to these standards or meet such requirements
• Drive/execute data quality assurance practices
• Support data management solutions pre-sales initiatives, proposal development and provide post-sales support

Requirements:

• At least 2 – 3 years’ work experience in data engineering field, experience with master data management, data governance, data lifecycle management
• Education qualification in Computer Science, Data Science, Machine Learning or relevant field
• Proficiency with relational/non-relational/NoSQL database and enterprise data warehouse/mart
• Experience with big data technologies e.g. Hadoop, Spark, Hive, HBase etc.

Interested candidates may whatsapp your resume to 6421 4965. Only shortlisted applicants will be contacted.

Cassie Chan | R2197426

Talentsis Pte Ltd | EA No: 20C0312

PRISM+ is the largest Singaporean direct-to-consumer smart home appliances brand. Our mission is to offer cutting-edge products to the masses at affordable prices. We are a rapidly growing, ever-evolving organisation, and we are seeking new teammates to join us on our exciting journey.

The Data Analyst is responsible for involves implementation of best practices, process improvements and developing monitoring dashboards for our Aircon Team.

Responsibilities:

• Extract, clean and present data in an understandable manner to the leads in the AC team.
• Interpret and analyze trends, patterns, and anomalies within the data to provide recommendations for business improvements related to air conditioning operations.
• Generate detailed reports and dashboards to present insights and support decision-making processes.
• Assist in identifying and addressing suggest improvements to address quality-related issues
• Work closely with business stakeholders to understand data needs and define analytical requirements.
• Collate and Maintain a repository of SOP and training materials for the department
• Contribute to team projects aimed at improving various aspects of operations
• To establish and maintain a relational database and recommend best practices for data storage, management and its upkeep.

• Diploma or Bachelor's Degree in Data Analytics/Science or a related field
• Proficiency in data analysis tools such as Python, SQL, and Excel
• Strong knowledge of data visualization tools (e.g., Tableau, Power BI) and ability to present data insights effectively.
• Excellent problem-solving skills and ability to work with large and complex datasets.
• Strong communication skills, with the ability to present technical findings to non-technical stakeholders.