801 Lead Data Scientist jobs in Singapore

Job Summary:

We are seeking an accomplished Senior Data Scientist to spearhead the development of advanced data-driven solutions. This role will involve utilizing large-scale financial datasets to create end-to-end analytics models, fostering a culture of innovation and quantitative excellence.

• Develop predictive modeling algorithms for pricing and dynamic campaign optimization using complex financial data.
• Conduct in-depth research on trade-offs between different quantitative methods and assess their applicability.
• Design and implement AI/ML models, ensuring high algorithm efficiency through parallel computing techniques and concurrent programming.
• Refactor code into reusable libraries, tools, and APIs, deploying machine learning ecosystems and performing sub-system integration as required.

Education & Experience

• Master's degree in Data Science, Computer Science, Statistics, Operations Research, or related quantitative field
• 5-7 years of hands-on experience in machine learning and data science roles
• Demonstrated experience working with location-based or IoT sensor data
• Previous exposure to healthcare data environments strongly preferred

Technical Skills

• Programming: Expert-level proficiency in Python or R, with strong experience in data manipulation libraries (pandas, numpy, dplyr)
• Machine Learning: Hands-on experience with scikit-learn, TensorFlow, PyTorch, or similar frameworks
• Spatial Analytics: Proficiency with spatial analysis tools such as GeoPandas, PostGIS, QGIS, or ArcGIS
• Databases: Experience with SQL and spatial databases (PostgreSQL/PostGIS, MongoDB with geospatial features)
• Visualization: Strong skills in creating compelling data visualizations using matplotlib, plotly, seaborn, or similar tools
• Statistical Analysis: Solid foundation in statistical methods, hypothesis testing, and experimental design

Domain Knowledge

• Understanding of healthcare workflows, hospital operations, or facility management
• Familiarity with RTLS technologies (RFID, BLE, WiFi-based tracking, UWB)
• Knowledge of spatial optimization techniques and facility layout principles
• Experience with time-series analysis and forecasting methods

Preferred Qualifications

Advanced Technical Skills

• Experience with cloud platforms (AWS, Azure, GCP) and scalable data architectures
• Knowledge of streaming data processing (Apache Kafka, Spark Streaming)
• Familiarity with containerization (Docker, Kubernetes) and MLOps practices
• Experience with graph analytics and network analysis techniques
• Background in simulation modeling or discrete event simulation

Specialized Experience

• Previous work in healthcare analytics, particularly in operational efficiency
• Experience with facility planning software or space management systems
• Knowledge of hospital design principles and healthcare facility standards
• Background in industrial engineering or operations research
• Experience with A/B testing in operational environments

Leadership & Communication

• Proven track record of translating complex analytical insights into business value
• Experience mentoring junior data scientists or analysts
• Strong project management skills and ability to manage multiple priorities
• Publications or presentations at relevant conferences (healthcare informatics, spatial analytics)

Data Science Leader Role

As a leading expert in data science, you will oversee our initiatives and manage a high-performing team. This position combines deep technical expertise with people leadership to drive data-driven decision-making and solve complex business challenges.

About the Role

We are seeking a visionary Lead Data Scientist to spearhead our AI and advanced analytics initiatives within the health domain. This role is ideal for a seasoned professional who thrives at the intersection of cutting-edge technology, ethical AI, and strategic business impact. You will lead the development and deployment of high-impact data science solutions, drive innovation in Generative and Agentic AI, and champion responsible AI practices across the organization.

Key Responsibilities

• Model Development & Deployment: Build, test, deliver, and maintain robust data science and AI models that solve complex business challenges.
• Responsible AI Leadership: Embed the highest standards of AI ethics and responsible AI in all phases of model development and deployment.
• Business Alignment: Influence and translate strategic business objectives into actionable data science requirements.
• Health Pillar Support: Drive ideation and delivery of advanced analytics and AI solutions within the health vertical especially on AI based conversational chatbots.
• Conversational AI Ownership: Lead the design, development, and optimization of intelligent chatbots and conversational agents.
• Innovation & Thought Leadership: Continuously explore and implement best-in-class solutions in Generative and Agentic AI.
• Team Leadership: Mentor and work manage a high-performing team of data scientists and AI engineers, fostering a culture of collaboration and excellence.

Qualifications & Skills

• Education : Master’s or PhD in Data Science, Computer Science, AI, or related quantitative field
• Experience : 8+ years (Master’s) or 5+ years post-PhD in AI/Data Science
• Programming : Expert in Python, SQL, LangChain, Hugging Face
• Use-Case Experience : Preferably with conversational chatbots utilizing LLMs for intent detection, Geolocation Analytics, Churn Modelling, Cluster Analysis, Recommendation Engine
• Cloud Platforms : Hands-on experience with Azure or Google Cloud
• MLOps/AIOps : Experience in managing ML artifacts and LLM cost optimization is a strong plus
• Leadership : Proven track record managing delivery teams of data scientists and AI engineers
• Communication : Exceptional ability to communicate across technical and non-technical audiences
• Collaboration : Strong team player with cross-functional and cross-geography collaboration skills
• Problem Solving : Demonstrated critical thinking and analytical capabilities

This is a newly created position within the Chief Data Office of a Financial services client. It is both hands-on and strategic , requiring a deep technical background in data science and AI, combined with the ability to translate that knowledge into governance, risk controls, and enterprise frameworks .

Unlike traditional paper-based governance approaches, this role is about modernizing and automating governance processes , using advanced analytics, AI, and ML techniques. You will design control artefacts, test and evaluate models, and build frameworks that ensure responsible, secure, and effective use of AI across the organization.

This is a global role with high visibility, contributing directly to enterprise-wide transformation initiatives in AI and data risk management.

• AI/ML Risk & Governance
  Assess risks associated with data, cloud, and AI/ML models, including emerging areas such as Generative AI.
  Design and implement automated controls to replace manual governance processes.
  Develop frameworks to evaluate and monitor models, ensuring responsible and ethical AI.
• Technical Data Science Leadership
  Build and optimize ML models for anomaly detection, decision trees, and smart data quality checks.
  Create enterprise platforms for testing, validating, and continuously monitoring AI/ML use cases (including LLMs).
  Translate advanced algorithms into actionable governance solutions that manage AI risk.
• Solution Delivery & Collaboration
  Work with cross-functional teams (data engineers, developers, business SMEs) to deliver scalable AI governance solutions.
  Act as a bridge between technical AI/ML development and governance/risk functions.
  Provide leadership to a small team of data scientists and interns.
• Continuous Learning & Transformation
  Stay ahead of new AI regulations, cloud standards, and data governance requirements.
  Introduce innovative approaches to embedding governance into AI/ML development.

• Master’s degree in Data Science, Computer Science, or related field.
• ~10+ years’ experience in data science/analytics, with strong knowledge of machine learning, statistical modeling, and algorithm design.
• Proven ability to build and manage end-to-end model pipelines (training, testing, deployment, monitoring).
• Strong Python skills, including use of relevant ML/AI libraries.
• Experience with cloud platforms (AWS, GCP, Azure) and hybrid/on-prem environments.
• Deep understanding of how algorithms work , beyond just API integration.
• Exposure to data risk, governance, or regulatory aspects of AI/ML is highly desirable.
• Excellent communication and stakeholder management skills; able to explain technical concepts in business/risk terms.
• Experience leading small teams or mentoring junior data scientists.

Those who are keen for the role and would like to discuss the opportunity further, please click "Apply Now" or email Kin Long at 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.

Kin Long Fok

Morgan McKinley Pte Ltd

EA Licence No: 11C5502 | EAP Registration No: R

Education & Experience

• Master's degree in Data Science, Computer Science, Statistics, Operations Research, or related quantitative field
• 5-7 years of hands-on experience in machine learning and data science roles
• Demonstrated experience working with location-based or IoT sensor data
• Previous exposure to healthcare data environments strongly preferred

Technical Skills

• Programming: Expert-level proficiency in Python or R, with strong experience in data manipulation libraries (pandas, numpy, dplyr)
• Machine Learning: Hands-on experience with scikit-learn, TensorFlow, PyTorch, or similar frameworks
• Spatial Analytics: Proficiency with spatial analysis tools such as GeoPandas, PostGIS, QGIS, or ArcGIS
• Databases: Experience with SQL and spatial databases (PostgreSQL/PostGIS, MongoDB with geospatial features)
• Visualization: Strong skills in creating compelling data visualizations using matplotlib, plotly, seaborn, or similar tools
• Statistical Analysis: Solid foundation in statistical methods, hypothesis testing, and experimental design

Domain Knowledge

• Understanding of healthcare workflows, hospital operations, or facility management
• Familiarity with RTLS technologies (RFID, BLE, WiFi-based tracking, UWB)
• Knowledge of spatial optimization techniques and facility layout principles
• Experience with time-series analysis and forecasting methods

Preferred Qualifications

Advanced Technical Skills

• Experience with cloud platforms (AWS, Azure, GCP) and scalable data architectures
• Knowledge of streaming data processing (Apache Kafka, Spark Streaming)
• Familiarity with containerization (Docker, Kubernetes) and MLOps practices
• Experience with graph analytics and network analysis techniques
• Background in simulation modeling or discrete event simulation

Specialized Experience

• Previous work in healthcare analytics, particularly in operational efficiency
• Experience with facility planning software or space management systems
• Knowledge of hospital design principles and healthcare facility standards
• Background in industrial engineering or operations research
• Experience with A/B testing in operational environments

Leadership & Communication

• Proven track record of translating complex analytical insights into business value
• Experience mentoring junior data scientists or analysts
• Strong project management skills and ability to manage multiple priorities
• Publications or presentations at relevant conferences (healthcare informatics, spatial analytics)

Machine Learning Engineer page is loadedMachine Learning Engineer Apply remote type Onsite locations Singapore, Singapore time type Full time posted on Posted Yesterday time left to apply End Date: October 30, 2025 (30+ days left to apply) job requisition id R

Machine Learning Engineer

In the rapidly moving Artificial Intelligence era, few spaces are moving faster than the AI-enabled PC. As a leading provider of world-class technology, this means bringing more intelligence into the PC ecosystem, enabling superior performance, enhanced productivity, and delightful experiences while maintaining privacy and security. We’re developing innovative approaches to introducing intelligence across our client PC portfolio by leveraging current methodologies, models, and tools to develop a robust end-user ecosystem. What’s more, we are collaborating with leading AI technology companies, academics, industry experts, and skilled engineers to deliver cutting-edge solutions that redefine the user experience.

Join us to do the best work of your career and make a profound social impact as a Machine Learning Engineer on our Client Solutions Group (CSG) Chief Technology Officer (CTO) Advanced Architectures Team in the Singapore Design Center .

.
What you’ll achieve

As a Machine Learning Engineer on the CSG CTO Advanced Architectures team, you’ll gain applied data science experience, working on a team of data scientists and embedded software engineers on Artificial Intelligence and Machine Learning solutions across the client devices portfolio. In this role, you will be responsible for realizing CTO AI initiatives, implementing algorithms, working with data scientists, data, and embedded SW engineers to rapidly develop, and deploy AI-enabled solutions for millions of end users.

You will:

• Work with engineering teams to integrate and deploy AI applications on client devices with backend cloud integration
• Work across a diverse set of telemetry collection and deployment environments inclusive of client AI/ML frameworks, endpoint & real-time OSes, and embedded firmware ecosystems
• Develop AI/ML software solutions tailored for client silicon using strong knowledge of client device ecosystem nuances and complexities
• Conduct experiments to train, tune, and optimize Machine Learning / Deep Learning models for delivery onto client devices
• Translate business questions into compelling use cases and provide insights using data and statistical methods as well as tell stories using data; Advocate and execute strategies to adopt data and data science in all business and technical conclusions

Take the first step towards your dream career
Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:

Essential Requirements

• Master's degree or higher in AI/ML, Computer Science, Statistics, Mathematics, or other Engineering & Scientific fields with a significant quantitative component; Bachelors + 5 years, MS + 3 years minimum, or PhD.
• Some experience developing for Microsoft (MS) Windows OS including client Software Development Kits (SDKs), MS DirectML, WinML, MS Graph, and experience with embedded device development in at least one RTOS
• Solid knowledge of AI/ML optimization techniques for delivering models and algorithms into resource-constrained environments including the ability to deliver AI / ML algorithms using one or more of C, C++, and Microsoft C#/.NET as well as strong experience with Deep Learning libraries and runtimes such as PyTorch, TensorFlow, TensorRT, and nuances of their application in Client ecosystems
• Good communicator with the ability to understand analytical methods and algorithms with a solid understanding of Large/Small Language Models, Machine Learning, Deep Learning, and Generative AI.
• Experience working in software development or other cross-functional teams

Desirable Requirements

• Bachelor’s degree / Master’s degree, solid knowledge and application of engineering concepts along with effective problem-solving ability
• Familiarity with development in real-time embedded environments and experience working with Open Neural Network Exchange (ONNX) models and the ONNX run time (ORT)as well as experience with at least one major hardware vendor toolchain such as Intel OpenVino, Qualcomm QNN, NVIDIA CUDA, or AMD Ryzen AI Software

Who we are

We believe that each of us has the power to make an impact. That’s why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you.

Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.

Application closing date: 30 October 2025

Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here .

Dell Technologies helps organizations and individuals build their digital future and transform how they work, live and play. The company provides customers with the industry’s broadest and most innovative technology and services portfolio for the data era.

As a Machine Learning Engineer (Trading & Financial Intelligence), you will contribute to the development of AI-powered systems and autonomous agents that transform how financial analysis and decision-making are conducted. Working under the guidance of senior team members, you will help build intelligent solutions that analyze markets, extract insights from financial data, and support risk management using machine learning and quantitative techniques. This role offers an excellent opportunity to learn and apply both traditional ML and modern LLM-based approaches to solve real financial problems while collaborating with experienced trading, research, and product teams.

• Assist in designing and implementing machine learning solutions for financial markets, from predictive models to AI agents powered by LLMs
• Support the development of intelligent systems using traditional ML approaches (time series analysis, anomaly detection, pattern recognition) and modern agentic frameworks
• Help apply quantitative methods and data mining techniques to extract insights from financial datasets under senior guidance
• Contribute to building ML pipelines for model development, backtesting, and production deployment with monitoring frameworks
• Support research platforms that enable experimentation with both classical statistical models and LLM-based approaches for financial analysis
• Work closely with traders, quants, researchers, and senior engineers to understand and help solve complex financial problems
• Assist in developing risk assessment and portfolio optimization systems using quantitative methods and AI-driven approaches
• Participate in code reviews, documentation, and knowledge sharing to continuously improve technical skills

• We welcome all applicants who are eligible to work in Singapore
• Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Mathematics, Physics, Financial Engineering, or related quantitative field
• 0-2 years of professional experience in machine learning, data science, or software engineering (internships, projects, and academic experience count)
• Solid programming skills in Python with familiarity with scientific computing libraries (pandas, numpy, scikit-learn)
• Foundational knowledge of machine learning including supervised/unsupervised learning, basic deep learning concepts, and statistical modeling
• Interest in Large Language Models and modern AI techniques - experience with prompt engineering, fine-tuning, or agentic systems is a plus but not required
• Strong mathematical and analytical foundation with ability to learn and apply quantitative concepts to practical problems
• Experience with data manipulation and basic feature engineering from structured datasets
• Eagerness to learn with ability to work collaboratively in a mentorship-oriented environment
• Good communication skills to discuss technical concepts and ask questions effectively
• Basic understanding of software engineering practices including version control (Git) and testing
• Curiosity about financial markets - prior knowledge of trading systems or quantitative finance is beneficial but not required
• Academic or personal projects demonstrating ML skills through coursework, competitions, or self-directed learning

About Unravel Carbon

At Unravel Carbon, we're on a mission to accelerate the world's transition to a zero-carbon economy. We're a team of entrepreneurs, engineers, and climate experts who believe that data and AI are the keys to unlocking a sustainable future. Our Sustainability AI agents platform helps companies across the globe to measure, reduce, and report their carbon emissions with unprecedented accuracy and efficiency. We're backed by top-tier investors like Sequoia and Y Combinator, and we're growing fast.

Our culture is built on a foundation of intellectual honesty, extreme ownership, and a relentless focus on results. We're a fun, collaborative, and purpose-driven team that isn't afraid to tackle the world's biggest challenges. If you're ready to do the best work of your life and make a real impact, we want to hear from you.

About The Role

We are looking for an early-career ML Engineer with a focus on Generative AI to join our early, growing team. It is a great opportunity to join a company that can have a material impact on fighting climate change.

As the Machine Learning team, we strive to design and build AI products and systems that are reliable, scalable, and maintainable. Some of the traits that we promote within the team are ownership, curiosity, transparency, and a strong writing culture. As an early team member, you will be expected to help shape our product direction and to strengthen the team's culture. You will collaborate closely with product managers, software engineers, designers, data engineers, and sustainability experts to ship products that create value and solve problems for our customers.

What You Will Work On

• Build AI agents for sustainability professionals that automate emissions calculations, extract insights from emissions inventory, generate sustainability reports, and streamline other key sustainability workflows.
• Develop LLM-powered systems that process and understand sustainability data from various sources like invoices, utility bills, and supply chain documents.
• Build agentic workflows that combine language models with structured data processing and domain-specific reasoning capabilities.
• Continuously improve our multi-ML model (semantic search and text classification) carbon engine that calculates carbon emissions, using millions of lines of transactional data and our proprietary data set of carbon emission factors.
• Design and build scalable, modular ML services on AWS infrastructure that serve both traditional ML models (transformer-based models like ModernBERT, T5) and LLM-based systems in production.
• Implement evaluation frameworks and quality controls for LLM-based systems to ensure reliable performance in production.
• Lead our efforts to build AI-powered systems that leverage our various data sets to automatically identify and recommend decarbonization solutions for our customers.

About You

• You have 1-3 years of experience in Machine Learning, Generative AI or are an upcoming new graduate with extensive relevant internships.
• You have strong experience in Python, SQL and are comfortable with modern ML frameworks like transformers, LangChain, or similar libraries.
• You are familiar with LLMs, prompt engineering, and have worked with LLM APIs or built RAG systems.
• You have shipped NLP/ML solutions to production and can demonstrate the impact of your work.
• You are able to own the entire lifecycle of a Machine Learning project. You don't need to be an expert on every aspect of it, but you must be a quick learner to pick things up and go deep when needed.
• You have an understanding of system design and can build scalable ML services.
• You like to think through product problems and enjoy working cross-functionally.
• You use solid engineering practices, write maintainable code, and care about code quality.
• You are proficient with AI-based coding tools and use them effectively in your workflow.
• You thrive in a fast-paced environment and can adapt quickly to changing priorities.
• You enjoy mentoring others where you can.

BONUS POINTS IF

• You have experience with LLM evaluation, guardrails, or agent frameworks.
• You have worked with vector databases and embedding systems.
• You have domain knowledge in sustainability, carbon accounting, or climate tech.
• You have a Master or PhD degree in Computer Science, Applied Computing, Computational Linguistics, Machine Learning or a related field.

What You’ll Gain

• Opportunity to shape product direction and team culture at a fast-growing climate tech startup backed by top-tier investors.
• Work directly with founders and senior leadership on products that have material impact on fighting climate change.
• Gain deep expertise in applying cutting-edge AI techniques to solve critical sustainability challenges.
• Experience building production AI systems at scale while contributing to the world's transition to a zero-carbon economy.