1. Position Summary

We are looking for a Data Engineer to join our team and contribute to a major project within the semiconductor manufacturing domain. The role involves designing and implementing data pipelines, managing Oracle-based data environments, and supporting end-to-end BI processes — from data ingestion to visualization. This position is based on-site at our partner’s advanced manufacturing facility, offering hands-on exposure to large-scale industrial data systems.

2. Key Responsibilities

• Design, develop, and maintain Python-based applications and APIs to extract, transform, and deliver data in JSON format.
• Design and create robust data models to support efficient querying and reporting.
• Define relationships, hierarchies, and calculated columns/measures that align with business logic.
• Design, develop, and maintain data pipelines and ETL workflows for manufacturing data (ERP, MES, SPC, FDC, etc.).
• Implement and optimize database logic, including stored procedures, functions, and PL/SQL scripts.
• Build and manage staging schemas, data validation processes, and data transformation logic.
• Develop and maintain data marts and dimensional models to support analytics and reporting.
• Collaborate with BI developers and analysts to deliver Power BI dashboards, KPI reports, and visual analytics.
• Ensure data accuracy, consistency, and completeness across multiple source systems.
• Support data governance, documentation, and performance tuning efforts.
• Partner with internal and external stakeholders to ensure timely and high-quality data delivery for business use.
• Perform any ad-hoc duties assigned by the Company as and when required.

3. Qualifications& Skills

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• Minimum 3 years of experience in data engineering, data integration, or BI development.
• Proficient in Python programming, specifically for data extraction, API development, and JSON data manipulation.
• Strong understanding of data warehousing concepts, schema design, and ETL best practices.
• Solid working experience with relational databases (e.g. Oracle, SQL Server, MySQL, PostgreSQL), including stored procedures and query optimization.
• Proficient with ETL tools such as Pentaho Kettle, Informatica, Talend, or similar.
• Experience developing reports and dashboards in Power BI (or Tableau/Qlik).
• Familiarity with SQL pipelines, data validation, and data replication tools.
• Strong analytical and problem-solving mindset with attention to data quality and performance.
• Ability to work collaboratively with business, IT, and engineering teams in fast-paced environments.
• Excellent documentation and communication skills.

4. Preferred /Additional

• Experience in semiconductor or manufacturing systems (ERP, MES, SPC, FDC) preferred.
• Exposure to data replication frameworks (Oracle Golden Gate, SharePlex, AWS Glue) is an advantage.
• Experience developing custom Python applications/APIs for data extraction and familiarity with JSON data structures is highly preferred.
• Familiarity with cloud-based data warehouses (Snowflake, Redshift, Synapse) and Giga Report is a plus
• Knowledge of data governance frameworks, metadata management, and data security best practices.

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data

operations and support function in a cloud-first environment. The ideal

candidate will bring strong technical leadership, hands-on expertise in AWS

and Snowflake, and proven experience in managing Business-As-Usual (BAU)

data platforms, production support, and continuous improvement initiatives.

▪ Develop tools to improve data flows between internal/external systems

and the data lake/warehouse.

▪ Work with stakeholders to understand needs for data structure, availability,

scalability, and accessibility.

▪ Build robust and reproducible data ingest pipelines to collect, clean,

harmonize, merge, and consolidate data sources.

▪ Understanding existing data applications and infrastructure architecture

▪ Build and support new data feeds for various Data Management layers and

Data Lakes

▪ Evaluate business needs and requirements.

▪ Support migration of existing data transformation jobs in Oracle, and MS[1]SQL to Snowflake.

▪ Lead the migration of the existing data transformation jobs in Oracle, Hive,

Impala etc. into Spark, Python on Glue etc.

▪ Able to document the processes and steps.

▪ Develop and maintain datasets.

▪ Improve data quality and efficiency.

▪ Lead Business requirements and deliver accordingly.

▪ Collaborate with Data Scientists, Architect and Team on several Data

Analytics projects.

▪ Collaborate with DevOps Engineer to improve system deployment and

monitoring process.

▪ Experience in critical production support and how the BAU functions is

preferred.

Requirements Key Skills:

▪ Lead a team of data engineers in managing day-to-day BAU operations,

production support, incident management, and platform stability.

▪ Strong AWS knowledge in terms of designing new architecture and

providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA,

AMS, IAM).

▪ In-depth knowledge with respect to Snowflake and its architecture.

▪ Prefer prior Experience in BAU environment.

▪ Good knowledge on Airflow and MWAA.

▪ Hands-on experience in SQL/Python/Pyspark.

▪ Expertise in optimizing techniques in cloud environments.

▪ Should have the vision on data strategy and able to deliver the same.

▪ Should be able to lead the design and implementation of data management

processes, including data sourcing, integration, and transformation.

▪ Able to manage and lead a team of data professionals, providing guidance,

mentoring and foster a collaborative and innovative team culture focused on

continuous improvement.

▪ To evaluate and recommend data-related technologies, tools, and

platforms.

▪ Collaborate with IT teams to ensure seamless integration of data solutions.

▪ Should have experience in Implementing and enforcing data security

protocols and ensure compliance with relevant regulations.

Required Qualifications:

▪ At least 8+ years of Data Engineer Experience

▪ Bachelor qualification in a computer science or STEM (science, technology,

engineering, or mathematics) related field.

▪ At least 5+ years of recent hands-on professional experience (actively

coding) working as a Lead handling support & production issue.

▪ 2+ experience with large scale datasets, data lake and data warehouse

technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake

is highly preferred.

▪ At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon

RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step

Functions.

▪ Professional experience working in an agile, dynamic and customer-facing

environment is required.

▪ Understanding of distributed systems and cloud technologies (AWS) is

highly preferred.

▪ Understanding of data streaming and scalable data processing is preferred

to have.

▪ Strong knowledge in scripting languages like SQL ,Python, UNIX shell and

Spark is required.

▪ Understanding of RDBMS, Data ingestions, Data flows, Data Integrations

etc.

▪ Technical expertise with data models, data mining and segmentation

techniques.

▪ Experience with full SDLC lifecycle and Lean or Agile development

methodologies.

▪ Knowledge of CI/CD and GIT Deployments.

▪ Ability to work in team in diverse/ multiple stakeholder environment.

▪ Ability to communicate complex technology solutions to diverse teams

namely, technical, business and management teams

Soft Skills

▪ Ability to work in a collaborative environment and coach other team

members on coding practices, design principles, and implementation

patterns that lead to high quality maintainable solutions.

▪ Excellent communications and stake-holder management are required.

▪ Ability to handle senior leadership and report to them if required.

▪ Ability to work in a dynamic, agile environment within a geographically

distributed team.

▪ Ability to focus on promptly addressing customer needs.

▪ Ability to work within a diverse and inclusive team.

▪ Technically curious, self-motivated, versatile and solution-oriented

Data / ML Intern, BenefitBee

BenefitBee is a stealth-stage startup based in the US and Singapore, building AI-native infrastructure for the employee benefits world. The founding team has built and scaled venture-backed companies and brings operating experience from places like Wish, Meta, Blackrock and Mercer. If you join, you'll be learning directly from founders and operators who have done this at a serious scale.

Our vision
Employee benefits is a massive, deeply manual industry that still runs on PDFs, spreadsheets, and email. We think the entire workflow can be rebuilt around AI, turning messy, unstructured documents into structured intelligence that helps people make faster, better decisions. We're early and moving fast, and the people who join now will help shape both the product and the company.

What you'll work on

• Build Python pipelines to extract and clean unstructured text from insurance, medical, and academic documents

• Convert raw text into standardized schemas (JSON) that feed our downstream analytics

• Develop models to surface trends in claims, renewals, and preventative care outcomes

What we're looking for

• Pursuing or completed a degree in Data Science, CS, Math, Biomedical Engineering, or Bioinformatics

• Solid Python and a real grasp of evaluation metrics (Accuracy, AUC, F1, etc.)

• Hands-on experience parsing text from PDFs, spreadsheets, and other unstructured sources

• Bonus: you've wrangled genuinely ugly documents before and lived to tell the tale

You'll work directly with the founding team, ship things that go into the actual product, and see how an experienced team builds a company from zero.

Responsibilities:

• Lead and collaborate with data scientists and analysts to drive innovation, knowledge sharing, and continuous improvement.
• Design, develop, and deploy robust analytical and machine learning models using advanced statistical techniques.
• Partner with business and technical stakeholders to identify key challenges and translate them into data-driven solutions.
• Develop dashboards and data visualisations to effectively communicate insights to technical and non-technical audiences.
• Stay current with emerging data science trends, tools, and methodologies, applying relevant advancements where appropriate.
• Contribute to the establishment and enhancement of data governance, data quality, and analytics best practices.

Requirements

• Master’s degree or PhD in Data Science, Statistics, Machine Learning, Computer Science, or a related quantitative discipline.
• Significant hands-on experience in data science or advanced analytics roles, preferably within complex engineering or operational environments.
• Strong proficiency in Python and/or SQL, with experience using machine learning libraries and frameworks.
• Demonstrated ability to manage multiple projects concurrently and deliver high-quality outcomes in a fast-paced setting.
• Strong analytical and problem-solving skills, with the ability to interpret and extract insights from complex datasets.
• Excellent communication and stakeholder engagement skills, with the ability to explain technical concepts clearly to non-technical audiences.
• Familiarity with enterprise systems (e.g. PLM, MES, MRO) and cloud platforms such as AWS will be advantageous.

To submit your application, please apply online to apply@rn-care.com or call +(65) 6513 5697 for private and confidential discussion.

Your interest will be treated with the strictest of confidence. We regret that only shortlisted candidates will be notified or contacted.

RN Care Pte. Ltd
EA License No: 17C8900

We are seeking an experienced Data Architecture & Innovation specialist to drive enterprise-wide data and innovation initiatives across the organization.

This role will be responsible for shaping the enterprise data landscape, governing data architecture, evaluating emerging technologies, and driving business transformation through innovative solutions. The successful candidate will work closely with business and technology stakeholders to deliver scalable, future-ready platforms and improve operational efficiency.

Key Responsibilities

Data Architecture & Technology Innovation

• Define and govern enterprise data architecture, including Data Fabric and integration frameworks.
• Evaluate and implement emerging technologies such as AI, IoT, automation, and advanced analytics platforms.
• Drive enterprise-wide data transformation initiatives and technology adoption.

Data Platforms & Integration

• Oversee the architecture and integration of enterprise data platforms and interfaces.
• Collaborate with internal teams and technology partners to ensure scalable, secure, and efficient data solutions.
• Establish best practices for data integration, interoperability, and platform governance.

Business Transformation & Process Optimisation

• Identify opportunities to improve business processes through technology, automation, and AI-driven solutions.
• Lead initiatives to improve operational efficiency and deliver measurable business value.
• Develop and execute innovation roadmaps aligned with business objectives.

Stakeholder & Vendor Management

• Partner closely with business, IT, and external vendors to deliver strategic technology initiatives.
• Present recommendations, architecture designs, and innovation strategies to senior management.
• Manage vendor engagements, project deliverables, and implementation activities.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline.
• Minimum 7 years of experience in Data Architecture, Enterprise Architecture, Data Platforms, or Technology Innovation.
• Strong experience in enterprise data architecture, data platforms, and integration technologies.
• Experience with Data Fabric architectures, data integration frameworks, and enterprise data ecosystems.
• Good understanding of emerging technologies such as AI, automation, IoT, and advanced analytics.
• Experience with analytics and visualization tools such as Tableau and Power BI will be advantageous.
• Strong stakeholder management, communication, and project leadership skills.
• Experience in process optimisation, digital transformation, or enterprise innovation initiatives is highly preferred.

Preferred Skills

• Knowledge of automation technologies and RPA solutions.
• Familiarity with enterprise architecture principles and governance frameworks.
• Exposure to Lean, Six Sigma, or process improvement methodologies will be an advantage.

Those who are keen for the role and would like to discuss the opportunity further, please click "Apply Now" or email Kin Long at kinlong.fok@quesscorp.sg with your updated CV.

Only shortlisted candidates will be responded to, therefore if you do not receive a response within 14 days, please accept this as notification that you have not been shortlisted.

Quess Selection & Services Pte Ltd

EA Licence No: 23C2060 | EAP Registration No: R2095054

This is in partnership with the Employment and Employability Institute Pte Ltd (“e2i”).

e2i is the empowering network for workers and employers seeking employment and employability solutions. e2i serves as a bridge between workers and employers, connecting with workers to offer job security through job-matching, career guidance and skills upgrading services, and partnering employers to address their manpower needs through recruitment, training, and job redesign solutions. e2i is a tripartite initiative of the National Trades Union Congress set up to support nation-wide manpower and skills upgrading initiatives. By applying for this role, you consent to Quesscorp Singapore’s PDPA and e2i’s PDPA

Responsibilities

1. Perform duty to manage data centre (DC)operations, maintenance, troubleshooting, project rollout and facilities related matters.

2. Perform DC monitoring and maintenance on infrastructure systems, critical facilities and associated equipment.

3. Perform preventive and corrective support to scheduled or unscheduled maintenance on DC

infrastructure systems, critical facilities equipment and/or services.

4. Ensure all subcontractors deliver a quality and competent service and all contractual obligations are met. Supervise the vendors to all scheduled and adhoc activities related to DC facilities.

5. Perform DC and critical facilities work on environmental and management programs

6. Perform equipment functionality test and data analysis

7. Perform assets management duty, includingmaintaining of inventory, change and control programs and purchase of parts and supplies

8. Promptly respond and attend to incident and/or emergency situations

9. Provide standby support upon activation for shift duty stand-in and/or other coverage

10. Conduct routine, sanity check and ongoing assessment of DCC infrastructure systems and critical facilities operations

Requirements:

• Nitec / Higher Nitec / Diploma in Electrical/Mechanical/DC Infrastructure or relevant engineering discipline (Electrical, Mechanical or related fields)
• Additional certifications relevant to the industry is an added advantage
• 1 -2 years experience maintaining electrical, mechanical, fire protection system in facility management, particularly handling critical systems would be an added plus
• Strong problem-solving abilities, communication skills, and the ability to work independently and as part of a team
• Proficient in Computer skills eg. microsoft office, google emails, docs etc

Junior Data Scientist – Business Operations & Analytics

Summary

We are seeking a highly analytical and strategic Junior Data Scientist to drive data-led decision making across a large-scale customer and business operations environment. This role will focus on leveraging advanced analytics, reporting, and data modelling to uncover actionable insights, improve operational performance, and influence business strategy. The ideal candidate thrives in ambiguous environments, can independently manage complex cross-functional initiatives, and is passionate about transforming data into meaningful business outcomes.

Responsibilities

• Develop and execute data science and analytics strategies that support business objectives and operational excellence.
• Design, build, and maintain advanced analytical models, prototypes, and frameworks to identify trends, opportunities, and performance improvements.
• Extract, process, and analyze large, complex datasets using SQL, Python, R, and Big Data technologies.
• Create and maintain scalable dashboards, reporting systems, KPIs, and operational metrics to support business performance monitoring.
• Translate complex analytical findings into clear, actionable recommendations for technical and non-technical stakeholders.
• Partner closely with cross-functional teams including Operations, Product, Engineering, and Business Leadership to solve complex business challenges.
• Drive data governance, reporting best practices, and continuous improvements in analytics methodologies.
• Mentor and support analysts and data professionals, fostering a culture of collaboration, innovation, and analytical excellence.
• Identify opportunities to automate reporting, streamline workflows, and improve operational efficiency through data-driven solutions.
• Present insights and strategic recommendations to senior leadership to influence decision-making and business direction.

Requirements

Essential

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative discipline.
• 2 - 3 years of experience in data analytics, data science, business intelligence, operations analytics, or a similar function.
• Advanced SQL skills, including the ability to build, optimize, and maintain complex queries against large datasets.
• Experience working with Big Data technologies and analytical tools such as Tableau, Hive, Presto, Python, and/or R.
• Strong understanding of operational metrics, KPIs, reporting frameworks, and performance measurement methodologies.
• Proven ability to perform exploratory analysis and derive actionable insights from complex datasets.
• Experience designing dashboards, reports, and visualizations that support business decision-making.
• Excellent communication and stakeholder management skills, with the ability to explain technical concepts to diverse audiences.
• Strong problem-solving mindset with the ability to work independently in fast-paced and ambiguous environments.

Preferred

• Experience supporting Customer Operations, Customer Support, Scaled Operations, Shared Services, or Business Operations functions.
• Experience working with large-scale datasets in high-growth technology, digital, e-commerce, or platform-based organizations.
• Knowledge of data pipeline architecture, ETL processes, and data warehousing concepts.
• Exposure to machine learning, predictive analytics, forecasting, or statistical modelling techniques.
• Demonstrated track record of driving measurable business impact through data-driven initiatives.
• Experience mentoring analysts or leading cross-functional analytics projects.

This is an initial 12-months contract role

Our client, one of Asia-Pacific’s leading organizations is looking for:

Data Scientist

Responsibilities:

• Work with product owners, engineering teams, and industry partners throughout the product development lifecycle from concept, design, prototyping, acceptance testing, data curation, delivery, operationalisation, industry proliferation, to product end-of-life
• Develop and deploy software components based on microservices-based architecture
• Participate in agile secure software development processes and best practices, documentation of user requirements and software codes during the software development lifecycle
• Propose, implement, and validate algorithms, ensuring functional and non-functional requirements

Requirements:

• Degree in Engineering, Computer Science, Mathematics, Statistics or equivalent with strong technical knowledge in AI
• Good understanding of the latest research and technologies in AI for production deployment
• Strong coding experience in programming languages such as Python and/or C++
• Experience working with libraries for data manipulation, visualization, machine learning, and reporting.
• Hands-on experience with one or more deep learning frameworks, e.g., TensorFlow, Torch
• Extensive experience with OpenAI and Claude code-based prompt engineering; Hands-on experience developing and deploying AI Agents, RAG and vector/graph databases.
• Strong understanding of 3D geometry, vector math, and coordinate systems
• Proficiency in relevant 3D modeling or CAD software (e.g., Blender, Rivet) and/or programming libraries (e.g., OpenGL, CGAL, Three.js)

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Interested applicants can also email CV at harry@nsearchglobal.com (for faster processing, please state the exact job / position title applied “Data Scientist”

Only shortlisted candidates will be notified.

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EA License Number: 10C3636
EA Personnel Name: Arora, Hardeep
EA Personnel Registration Number: R1111454

By submitting your resume and cover letter to apply for our job opening, you confirm that you have read the Data Protection Notice for Job Applicants (https://www.nsearchglobal.com/dp-notice/job-applicants) and you consent to the collection, use, and disclosure of your personal data for the purpose of verifying and evaluating your job application. Additionally, you have to notify and obtain consent from all individuals listed as your references to their data being collected and disclosed for the purposes related to your job application

The intern will be attached to the Fleet Digital section and will support the team in the following activities: 

• Extract and analyze sets of data from multiple sources and database for Harbour Launch, Tugs and Crew Deployment; develop and test hypothesis and communicate with section managers recommendations. 

• Identify and interpret trends or patterns in the collected data sets. 

• Detect anomalies, spot discrepancies and possible defects from our Fleet Management System 

• Produce insights on operations data using analytic tools (Python/Excel/Power BI) 

• Design, develop and maintain ongoing reports and dashboards. 

• Take in the lead in digitalization projects by working with key stakeholders within and outside of organization. 

• Perform any other ad-hocs duties as assigned. 

Preferred Skills

• Proficiency in Python Programming Language and Excel VBA 

• Experience in UI/UX designing and able to develop dashboard with data visualization tools (Example: Power BI and Tableau) 

• Analytical mindset driven to understand machinery and operation data 

• Strong organizational and problem-solving skills 

• Commitment to learning including new analytical methods and Harbour Craft profile 

• Ability to identify data-driven insights and trends from large data sets, keeping in mind of data quality and accuracy 

• Able to develop Robotics Process Automation (RPA) – UiPath would be a plus. 

Data Analytics

• Spearhead the design and execution of end-to-end data analytics strategies.
• Develop and manage automated data pipelines and ETL workflows.
• Perform data cleaning, preprocessing, and validation to maintain high data accuracy and integrity.
• Utilize advanced statistical and data mining techniques to analyze extensive healthcare datasets.
• Build and maintain interactive dashboards with user-friendly visualizations tailored for non-technical stakeholders.
• Deliver in-depth analytics to support clinical research and quality improvement projects, especially in areas like chronic disease management (e.g., diabetes, kidney disease, asthma).
• Create predictive models and deploy machine learning solutions, including large language models (LLMs).
• Collaborate with clinical teams to integrate Patient-Reported Outcome Measures (PROMs) into existing care processes.
• Work closely with GTO and AIO teams to improve data visibility and accessibility.
• Design and apply LLM-based solutions to streamline and optimize patient care pathways.

Data Quality & Monitoring

• Conduct regular validation to ensure the integrity and consistency of datasets.
• Detect and interpret key trends, patterns, and insights from healthcare data.
• Establish and maintain robust data quality assurance and validation protocols.
• Generate and present clear, data-driven reports and visualizations to stakeholders.
• Ensure all data visualizations are user-centric and accessible to non-technical users.
• Liaise with cross-functional teams to gather and address their specific data requirements.

Data Governance & Protection

• Implement stringent data security policies and access controls.
• Supervise data standardization and quality management initiatives.
• Ensure adherence to data privacy laws such as PDPA and HBRA.
• Develop secure protocols for safe data exchange and collaborative access.
• Promote ethical AI usage and ensure responsible deployment of LLM technologies.

Key Requirements

• Bachelor’s degree in a quantitative field (e.g., Computer Science, Data Analytics, Statistics)
• Minimum of 2 years’ experience in healthcare analytics or a similar field.
• Strong programming skills in Python, R, and SQL.
• Hands-on experience with data visualization platforms such as Tableau, Power BI, or TIBCO Spotfire.
• Proficiency with cloud analytics environments, especially Databricks.
• Solid foundation in statistical methods, including predictive modeling, A/B testing, and time-series analysis.
• Skilled in deploying and fine-tuning AI/ML models, including LLMs, within healthcare contexts.
• Experience working with cloud providers, particularly AWS.
• Familiarity with container technologies like Docker and Kubernetes.
• Experience using modern web frameworks such as Streamlit, NextJS, and TypeScript.
• Proficient in REST API development using frameworks like FastAPI.
• Understanding of database design, with hands-on experience using tools like SQLAlchemy.
• Capable of working with large and complex datasets.
• Proficient in using Git for version control and collaborative coding.
• Strong grasp of CI/CD pipelines and DevSecOps best practices.
• Knowledge of medical terminology and healthcare IT systems.
• Demonstrated ability to manage stakeholders and drive successful project outcomes.
• Excellent analytical thinking and problem-solving capabilities.
• Effective communicator with strong presentation, writing, and interpersonal skills.
• Highly detail-oriented, with a commitment to accurate data handling and analysis.
• Able to convert business challenges into technical data solutions.
• Team-oriented, proactive, and capable of thriving under time constraints.
• Comfortable working both independently and collaboratively in dynamic environments.

To apply, please visit www.gmprecruit.com

We regret that only shortlisted candidates will be notified.

GMP Technologies (S) Pte Ltd | EA License: 11C3793 | EA Personnel: Bautista Gia Grace De Guzman | Registration No: R23111973

IT'S NEVER TOO LATE FOR A NEW BEGINNING OF YOUR LIFE

Love to Travel ? Looking for change of environment ? Just ORD? Just graduate?

Be part of the world’s leading Sales & Marketing Company and work with International clients across different countries! With a dynamic team that strives for high standard campaign execution, bringing great opportunities and unlimited growth.

Role:

• Face to face interaction with people
• Building customer relationship and maintaining positive brand awareness.

Benefits:

• Overseas Travelling Opportunities
• 1 to 1 Mentorship & Coaching
• Fun and Vibrant Environment
• Career Advancement

Requirements :

• Team Player
• Keen Learner
• Good Command of English
• No experience needed!

APPLY NOW!

Project Overview

This project aims to develop and clinically validate a real-time blood analysis and diagnostic platform using an integrated microfluidic medical device. The platform uses precision microfluidic technology to process and profile the biological activity of white blood cells, which is related to inflammatory conditions ranging from diabetes and sepsis to leukemia.

The Postdoctoral Research Associate - Data Scientist will lead the acquisition, preprocessing, analysis, and modelling of medical device-generated data, and will work closely with clinicians, scientists, and engineers to translate AI/machine learning models into working, deployable software for clinical testing and point-of-care use.

This role offers a rare opportunity to bridge clinical data science, medical device engineering, and translational research, moving from experimental and clinical sample data to robust AI-enabled diagnostic workflows and deployable prototypes.

Responsibilities

The Postdoctoral Research Associate - Data Scientist is responsible for developing end-to-end data and AI/ML workflows for the medical diagnostic platform, from device data acquisition and signal/data preprocessing to model optimisation, validation, software integration, and deployment.

Responsibilities include:

- Work closely with clinicians, scientists, software engineers, mechanical/electrical engineers, and data scientists to define clinical use cases, data requirements, model outputs, and deployment workflows for the medical device platform.

- Design and implement reliable data acquisition pipelines from medical device hardware, sensors, imaging or signal outputs, and associated experimental or clinical metadata.

- Develop preprocessing, quality-control, annotation, feature-engineering, and data-management workflows for noisy, multimodal, longitudinal, or time-series biomedical data.

- Analyse experimental and clinical sample data to characterise device and biological performance, identify artefacts, benchmark platform performance, and support evidence generation for translational studies.

- Develop, train, validate, and optimise machine learning, deep learning, statistical, or hybrid models for diagnostic, predictive, or decision-support tasks using appropriate metrics, cross-validation, robustness checks, and uncertainty analyses.

- Translate research models into reproducible and deployable software components, including model inference pipelines, APIs, dashboards, reports, or lightweight user interfaces for clinical and laboratory testing.

- Support software-hardware integration for data acquisition, model inference, device feedback, and prototype deployment; assist with basic UX refinement based on clinician and end-user feedback.

- Maintain high-quality documentation of datasets, code repositories, model versions, experimental protocols, validation results, data dictionaries, and technical reports.

- Prepare manuscripts, presentations, grant reports, and invention disclosures; contribute to literature reviews, patent/IP searches, and responsible research dissemination where relevant.

- Support clinical study workflows by coordinating with clinical collaborators and applying good data governance practices for sensitive clinical and experimental data.

Requirements

- Ph.D. in Data Science, Computer Science, Artificial Intelligence/Machine Learning, Biomedical Engineering, Electrical Engineering, Bioinformatics, Statistics, Applied Mathematics, Computational Biology, or a related field. Candidates close to completion may be considered if the degree will be conferred before appointment.

- Demonstrated research experience in data science, machine learning, deep learning, signal/image processing, biomedical data analysis, time-series analysis, clinical AI, or related computational research.

- Strong programming skills in Python; experience with common scientific and ML frameworks such as NumPy, pandas, scikit-learn, PyTorch or TensorFlow, Jupyter, and Git/GitHub.

- Experience with data acquisition, data cleaning, feature engineering, model optimisation, evaluation, reproducibility, version control, and scientific software development.

- Familiarity with clinical or biomedical datasets, medical device data, biosensor/microfluidic data, imaging data, physiological signals, or multimodal data integration is highly advantageous.

- Experience translating ML models into usable software prototypes, such as REST APIs, dashboards.

- Working knowledge of software-hardware interfacing, instrument-control software, serial/USB/Bluetooth communication, microcontrollers, embedded systems, or edge AI deployment would be advantageous.

- Ability to work closely with clinicians and multidisciplinary teams to interpret findings, gather end-user feedback, define clinical workflow needs, and improve the usability of AI/ML outputs.

- Strong written and oral communication skills, including the ability to write scientific manuscripts, technical documentation, reports, research proposals, and presentations for technical and non-technical audiences.

- Strong commitment to robust, ethical, and responsible AI/ML development, including attention to data privacy, model bias, interpretability, clinical validity, reproducibility, and safe deployment.

- Able and committed to work in Singapore, and willing to meet regularly with collaborators at NUS, NUH, and partnering hospitals.

Relevant Skills

Python, R/MATLAB, SQL, NumPy, pandas, scikit-learn, PyTorch/TensorFlow, Jupyter, data acquisition, biomedical signal processing, time-series analysis, image processing/computer vision, data preprocessing, feature engineering, model validation, model optimisation, uncertainty/robustness analysis, explainable AI, data visualisation, dashboards, REST APIs, Docker, Linux, Git/GitHub, MLOps, UX prototyping, software-hardware interfacing, and clinical data governance.

To apply, please visit our website at: https://portal.smart.mit.edu/careers/career-opportunities

Interested applicants are invited to send in their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.

Job Summary

We are looking for a Data Analyst to drive end-to-end analytics for Anti-Financial Crime projects in a reputed bank . This role blends strong analytical and data science capabilities with compelling storytelling, documentation excellence, and stakeholder leadership. You will work extensively on Hadoop Big Data, design analytic workflows, build ML models (including unsupervised techniques), and translate insights into meaningful business impact.

Mandatory Skill-set

• Bachelor’s/Master’s in Data Science, Statistics, Computer Science, Mathematics, Economics, or related fields;
• Must have 3+ years in Data Analytics, including exposure in Banking/Financial Services;
• Must have hands-on experience with Qlik Sense and Big Data tools;
• Strong expertise in SQL, Python ( Pandas, NumPy, Scikit-learn ) and PySpark;
• Strong understanding of machine learning, including unsupervised models;
• Excellent communication, consulting, slide creation, and stakeholder storytelling skills.

Desired Skill-set

• Certifications in Data Science, Cloud Technologies, or AML/Compliance;
• Experience in customer segmentation, anomaly detection, and analytics for financial crime;
• Understanding of model risk and regulatory expectations for model governance.

Responsibilities

• Analyze and work with business units on reported issues/queries relating to compliance surveillance systems;
• Process and analyze data related to AML/CFT investigations;
• Tuning and optimization of compliance surveillance systems;
• Tuning and optimization of Machine Learning Models in Compliance;
• Participate in compliance projects for compliance surveillance systems support and support in processing analytics data;
• Demonstrate proactive learning and adaptability to stay informed about regulatory changes and advancements in compliance technology;
• Effectively manage time and prioritize tasks to meet deadlines while maintaining high-quality outputs.

Should you be interested in this career opportunity, please send in your updated resume to apply@sciente.com at the earliest.

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EA License No. 07C563

Site Construction Manager with CSA and MEP work experience on Data Center Projects preferred.

Job Descriptions:

• Monitor and review master construction programme and preparation of catch-up programme if applicable
• Monitor and supervise Engineers/foreman, ensure compliance of the qualify procedure & standard of workmanship. Checking on quality and quantity of work by subcontractors
• Preparation of detailed programme for site team to follow accordingly and complete on time
• Resolve drawing discrepancies and technical difficulties with technical team
• Preparation of detailed method statements and work instructions for construction
• Coordinate between Private Client / sub-contractors /inter-departments and monitor site manpower and resources to meet schedules
• Liaise with the Design team on the submission of related CSA & MEP works and technical issues
• Plan all works on site, including programme schedules and construction methods, forecast equipment, material and manpower requirement usage etc
• Monitor progress against programme and cost against budget
• Promote and enforce a safe working environment
• Ensure works are compliant with the specifications and QA requirements

Job Requirements:

• Degree/Specialist Diploma in Civil Engineering/ Electrical Engineering / Mechanical Engineering or equivalent
• 10 years of relevant CSA & MEP project management experience i.e. RC works, Building works which includes experience in Data Center projects with 5 years in Site / Construction Manager roles and operational experience.

Key Responsibilities

• Work with product owners, engineering teams, and industry partners throughout the product development lifecycle from concept, design, prototyping, acceptance testing, data curation, delivery, operationalisation, industry proliferation, to product end-of-life
• Technical assessment on the maturity, viability, and suitability of AI research, technologies and trends that are relevant to the industry
• Develop and deploy software components based on microservices-based architecture
• Participate in agile secure software development processes and best practices, documentation of user requirements and software codes during the software development lifecycle
• Propose, implement, and validate algorithms, ensuring functional and non-functional requirements such as transparency, fairness, scalability, security, integration complexity and operational costs

Requirements

• Background in engineering, computer engineering, computer science, mathematics, statistics or equivalent
• Strong technical knowledge in AI
• Good understanding of the latest research and technologies in AI for production deployment
• Strong coding experience in programming languages such as Python and/or C++
• Experience working with libraries for data manipulation, visualization, machine learning, and reporting.
• Hands-on experience with one or more deep learning frameworks, e.g., TensorFlow, Torch
• Extensive experience with OpenAI and Claude code-based prompt engineering.
• Hands-on experience developing and deploying AI Agents, RAG and vector/graph databases.
• Strong understanding of 3D geometry, vector math, and coordinate systems
• Experience with algorithms for mesh manipulation, Boolean operations, and geometric transformations
• Proficiency in relevant 3D modeling or CAD software (e.g., Blender, Rivet) and/or programming libraries (e.g., OpenGL, CGAL, Three.js)
• Team player with the ability to work in a cross-functional team with excellent interpersonal skills
• Strong communication skills, both verbal and written, as well as strong presentation and engagement skills