918 Senior Data Scientist jobs in Singapore

Overview

Working Hours : Monday – Thursday (8.30am – 6pm), Friday (8.30am – 5.30pm) (Hybrid working arrangement)

Working Location : Punggol

Salary Package : Up to $8k

Employment type: Contract

• Design and conduct experiments to evaluate emerging SDG models (e.g., DDPM, ARF, Gaussian Copula).
• Investigate failure cases (e.g., when models fail with certain data types, size, or cardinality).
• Tune hyperparameters, refine architectures, and propose new modeling strategies.
• Collaborate with software engineers to build product features that require ML/DS input (e.g., imputation methods, handling of constraints, preprocessing pipelines).
• Recommend and develop suitable approaches for features like single-/multi-column constraints, imputation strategies, and privacy metrics.
• Work directly with users and the engineering team to diagnose user issues with training failures, poor outputs, or integration challenges.
• Provide actionable fixes and communicate technical insights in a user-friendly way.
• Write user-facing documentation pages. This could include explaining model choice, hyperparameters, and utility/privacy metrics in a user-friendly manner.
• Translate complex technical Data Science concepts into clear, approachable explanations.
• Work closely with the SWE team (Next.js, FastAPI, AWS) to integrate generation engine into production-ready systems.
• Participate in Agile rituals, code reviews, and design discussions.

• Bachelor’s degree or higher in Computer Science, Data Science, Business Analytics or a related field, with at least 2-3 years of relevant professional experience.
• Strong foundation in machine learning, with hands-on experience in model development and experimentation.
• Strong programming proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).

By submitting your resume, you consent to the collection, use, and disclosure of your personal information per ScienTec’s Privacy Policy (scientecconsulting.com/privacy-policy).

This authorizes us to:

• Contact you about potential opportunities.
• Delete personal data as it is not required at this application stage.
• All applications will be processed with strict confidence. Only shortlisted candidates will be contacted.

Wong Siew Ting (Maeve) - R

ScienTec Consulting Pte Ltd - 11C5781

What You’ll Do

• AI Solution Development
  • Conduct exploratory data analysis to extract insights and patterns that inform AI model design and development
  • Perform data cleaning, validation, and transformation (feature engineering) required by AI models
  • Design, develop, and evaluate AI models to address specific business needs
• AI Deployment and Operations
  • Deploy AI models into production environments, ensuring scalability, reliability, and performance
  • Implement and maintain model monitoring systems to track performance metrics and identify when models require retraining or adjustment.
  • Maintain reusable central feature store for AI model training and deployment
  • Implement automated pipelines for model training, validation, and deployment, adopting fit-for-purpose industry practices
• Stakeholder Engagement
  • Collaborate with cross-functional teams (e.g. data engineers, IT consultants, business users) to achieve project outcome
  • Present outputs from business analyses to HPB stakeholders, to translate data-driven insights into programme design and delivery

• Minimum 3 years of working experience in data science or developing AI/ML, including experience wrangling data in cloud-based analytics platforms and tools (e.g. Microsoft Azure, Databricks, Spark Ecosystems)
• Must be proficient in Python and possess adeptness with large-scale datasets.
• Bachelor / Master / PhD in Analytics, AI / Data Science, Computer Science, Engineering or Information Systems with major / project experience in data science and/or business analytics from a recognised university.
• o Professional certifications in business analytics / data science / ML engineering from accredited professional bodies coupled with a few years of related working experience for graduates from other disciplines, are also acceptable for the position
• Adaptive in a fast-paced matrix environment, overseeing multiple projects concurrently within an agile environment
• Possesses strong problem resolution, attention to detail and effective communication skills to manage and deliver complex projects involving internal and external stakeholders

Join to apply for the Data Scientist role at Hyundai Motor Group Innovation Center Singapore (HMGICS)

This position is responsible for applying data-driven problem-solving, data science, and optimization techniques to resolve real-life manufacturing problems and deploy the ideated solutions in a production environment.

HMGICS is seeking data scientists with a deep interest in solving real-life industrial problems and applying their solutions at scale in a mass-production environment. Candidates should have a technological interest in at least one of the following domains: Data Analytics, Optimization, AI/ML, or Generative AI & LLMs. Additionally, candidates should have a functional interest in at least one of the following areas: logistics, supply chain, assembly, quality, maintenance, or enterprise functions.

• Participate as a data scientist in multi-disciplinary project teams aiming to improve the performance of our production environment in specific areas such as logistics and supply chain, assembly, maintenance, and quality.
• Perform explanatory analytics to understand the key underlying drivers of performance and how to further optimize them.
• Develop and maintain optimization or predictive models as required to assist production in delivering productivity, flexibility, quality, or sustainability improvements.
• Deploy these models in production and train engineers and technicians to leverage the insights for improving their day-to-day performance.

What You'll Bring

• Bachelor's or Master's degree in Industrial Engineering, Computer Science, Mathematics, or equivalent practical experience.
• 2-5 years of project execution experience as a data scientist, resolving industrial problems across the value chain, including manufacturing, and ensuring the adoption of data science solutions.
• Preferred experience in the manufacturing and/or automotive industry.
• Strongly preferred experience in implementing data science and/or AI projects in real-life industrial environments (large POCs or at-scale deployments).
• Critical end-to-end problem-solving skills, including rapid and rigorous issue analysis, idea development and implementation, and feasibility demonstration and deployment at scale.
• Experience in applying Regression/Classification/Clustering models, Large scale data analysis, Time series analysis, Forecasting models, or Kernel-based methods.
• Experience in algorithm development using Mathematical programming (Linear programming, Mixed-integer programming), (Meta)Heuristic algorithms, Stochastic Process, or Combinatorial Optimization.
• Expertise in processing large-scale datasets in distributed data frameworks (Hadoop, Spark, or Hive).
• Expertise in data mining frameworks such as PyTorch, TensorFlow, Scikit-learn, or MLlib.
• Expertise in applying machine learning, Generative AI, LLMs is a plus.

• Entry level

• Full-time

• Engineering and Information Technology
• Industries: Motor Vehicle Manufacturing

Summary of the role

We’re looking for someone who is excited at the prospect of facing new and difficult data challenges. Someone who is comfortable working as part of a team who are building things from scratch. We’re looking for someone with deep technical skills, but who is really motivated by making an impact on our business and our customers.

• Use advanced analytics alongside, where necessary account-level reviews to monitor and assess the portfolios of our partners to ensure we obtain and maintain a deep understanding of where the existing and emerging risks are coming from.
• Build, implement and monitor new predictive rules and models which help us expand our capabilities around accurately understanding the level of risk the merchants our partners are presenting.
• Liaise with various payments firms and insurers to understand their needs and help shape the solutions we bring to market.

• 1-3 years experience conducting portfolio analysis in Python and extracting/manipulating data in SQL
• 1-3 years experience in consulting and/or start-up environments
• Commercial acumen and an understanding of the economics underpinning credit or payments portfolios
• Able to work autonomously and to display strong judgement and proactivity

• Experience with supervised models (e.g. logistic regression, gradient boosting) and unsupervised methods (e.g. clustering, anomaly detection).
• Experience in a role embedded within a risk team (could be fraud, credit or similar)
• Professional experience in the financial services industry
• LLM prompt management or agentic experience
• The ability to understand overall company economics and to read financial statements

Note: The nice-to-have qualifications are not mandatory but would be considered as additional strengths for the role.

• Flexible, remote-first working arrangements.
• Opportunities for significant professional growth and advancement within a company at the forefront of transforming risk management in payments.
• Globally-focused company, with exposure to Asian, European and American markets.
• A competitive compensation package, including company equity and performance incentives.
• Private healthcare employee insurance

At Envisso, we believe in the power of diverse teams to drive innovation. We are committed to fostering a collaborative, supportive, and inclusive environment. If you are ready to play a crucial role in shaping the future of payment risk management, we would love to hear from you!

Overview

Working Hours : Monday – Thursday (8.30am – 6pm), Friday (8.30am – 5.30pm) (Hybrid working arrangement)

Working Location : Punggol

Salary Package : Up to $8k

Employment type: Contract

• Design and conduct experiments to evaluate emerging SDG models (e.g., DDPM, ARF, Gaussian Copula).
• Investigate failure cases (e.g., when models fail with certain data types, size, or cardinality).
• Tune hyperparameters, refine architectures, and propose new modeling strategies.
• Collaborate with software engineers to build product features that require ML/DS input (e.g., imputation methods, handling of constraints, preprocessing pipelines).
• Recommend and develop suitable approaches for features like single-/multi-column constraints, imputation strategies, and privacy metrics.
• Work directly with users and the engineering team to diagnose user issues with training failures, poor outputs, or integration challenges.
• Provide actionable fixes and communicate technical insights in a user-friendly way.
• Write user-facing documentation pages. This could include explaining model choice, hyperparameters, and utility/privacy metrics in a user-friendly manner.
• Translate complex technical Data Science concepts into clear, approachable explanations.
• Work closely with the SWE team (Next.js, FastAPI, AWS) to integrate generation engine into production-ready systems.
• Participate in Agile rituals, code reviews, and design discussions.

• Bachelor’s degree or higher in Computer Science, Data Science, Business Analytics or a related field, with at least 2-3 years of relevant professional experience.
• Strong foundation in machine learning, with hands-on experience in model development and experimentation.
• Strong programming proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).

By submitting your resume, you consent to the collection, use, and disclosure of your personal information per ScienTec’s Privacy Policy (scientecconsulting.com/privacy-policy).

This authorizes us to:

• Contact you about potential opportunities.
• Delete personal data as it is not required at this application stage.
• All applications will be processed with strict confidence. Only shortlisted candidates will be contacted.

Wong Siew Ting (Maeve) - R

ScienTec Consulting Pte Ltd - 11C5781

Overview

Lynx Analytics was founded in 2010 by a group of INSEAD students and professors with a strong research background in graph analytics. Our founding purpose is to apply graph theory to simplify and solve complex, real-world business problems. Our mission has evolved, and we currently offer a range of cutting edge data analytics and AI solutions to help companies transform their operations and optimise their commercial performance. We work with a diverse and inclusive global team comprising professors, PhDs, MScs, and MBAs from Ivy Leagues, INSEAD and NUS with a broad spectrum of experience in start-ups and blue-chip companies. It is the combination of industry insight and experience, scalable proprietary technology, and highly qualified people that drives our compelling value proposition.

We are looking for ambitious, innovative, empathetic and relentless team players to explore the career opportunities that we offer as we continue to scale our operations. If you have a burning passion for data, Generative AI, and an interest to work in projects with international clients, this might just be the role for you!

You will as a Data Scientist work on and lead complex data analysis projects using standard modelling and data transformation approaches, Generative AI (including LLMs) as well as Lynx’s proprietary graph analysis system. You should be comfortable working with very large data sets residing in different data stores in disparate formats and be strong with hands-on implementation, as well as have the potential to move fast onto a high-growth career trajectory. Leadership experience and charisma are a huge advantage.

• Designing and delivering solutions for a defined Data Science related problem at the client’s location
• Present the results / prepare presentations for the project stakeholders (collaborating with the lead data scientist)
• Create reusable documentation, presentations, and code libraries during the projects
• Mentoring Data Science interns
• Leading smaller data science tasks with the help of internal leadership and PMO
• Participating in internal education and research tasks

• 3+ years of overall experience in data mining and/or data science field
• Mathematics, Statistics, Economics, Computer Science, Engineering or related degree (MSc or Ph.D. is preferred)
• Understanding complex data science solutions
• Solid knowledge of probability theory, statistics, data science algorithms, and their application in customer retention, campaign management, etc. areas
• Good communication (both verbal and written) and data visualization skills
• Coding abilities in at least one of the following languages: Python (preferred), R, SAS, C, JAVA, or similar
• Solid knowledge of DWH querying languages

Job Description

• Facilitate discussions with stakeholders to understand their business challenges, sharpen the business use cases and translate them into data science projects
• Perform data cleaning, pre-processing, feature engineering, and build data science models to address the use case
• Present findings, solicit feedback and prioritise refinements to the analysis in close iteration with stakeholders while managing overall project timeline
• Communicate the data insights in a clear and compelling narrative, supported with impactful visuals, to influence key decision makers
• Depending on the use case, design of dashboards and interactive visualisations as tools for data exploration and storytelling may be expected
• Capable of translating business use cases into analytical problems, and identifying appropriate data sources to tackle these problems.

• Proficient in writing scripts for data preparation and analysis, using modern analysis tools & programming methodologies.
• Proficient cleaning, imputing and correcting anomalies in the collected structured or unstructured data to ensure a high standard of quality in data sets to be used in the analysis work.
• Proficient in exploring and analysing datasets, applying probability and statistical methodologies and techniques to discover insights from the data.
• Proficient in building machine learning models to identify, recognise patterns and make predictions.
• Proficient in design principles and use of visualisations to best convey the intended information.
• Experience working in Government Sector.

Overview

We are an established, globally active management consulting company with offices in Switzerland, Germany, Austria, UK, USA, Singapore, Hong Kong, the Philippines, Australia, Indonesia and India. We are a valued partner to many of the world ’s largest international financial services and insurance firms. We support our clients at all project management stages from the development of strategies and operational frameworks to the technical implementation and handover. Our expertise in business and technology combined with our methodical approach enable us to create sustainable added value for our clients' business.

While Synpulse Singapore has a hybrid work policy, this role involves integrating with client teams and their specific work arrangements for successful project delivery. We look for candidates who can seamlessly adapt.

This role placement, which could be contractual, depends on your skillset, interview performance and the client project you are assigned to. We will provide full details about your client engagement and employment type before your start date.

• Identify data sources and automate collection processes
• Process structured and unstructured data
• Analyse information to discover trends and patters
• Build predictive models and machine learning algorithms
• Present information using data visualisation techniques
• Propose solutions and strategies to business challenges including facilitating workshops for relevant stakeholders, preferably using agile software development practices

• BSc (or above) in Statistics, Mathematics, Computer Science, Engineering or relevant field
• At least 3 years of working experience in data science
• Has experience working with LLMs and other Gen AI techniques
• Understanding of applied statistics, Mathematics and building supervised and unsupervised machine learning models
• Applied knowledge in Python, R, Power BI, Scala and/or SQL and Jupyter notebook
• Demonstrated ability to evaluate statistical models such as Machine Learning, Optimisation and Neutral Networks and other approaches to AI
• Demonstrated ability to transform ways of work with particular interest in Financial Services (Banking & Insurance) sector

• Adaptable schedules offering full-time roles and hybrid work options
• Attractive fringe benefits and salary structures in line with the market
• Modern and central office space with good public transport connections
• Can-do mentality and one-spirit culture
• Varied events and employee initiatives

• Resume
• Job references
• Qualifications (bachelor/ master diploma, etc.) with certificate of grades
• Motivation letter: Why Synpulse? Why you? Why this function?
• Recommendation letters (optional)

Do you approach your tasks with commitment and enjoyment, and are you convinced that teamwork achieves better results than working alone? Are you proactive and willing to go the extra mile for your clients? Are you motivated not only to design solutions but also to implement them? As a flexible and goal-oriented person, you will quickly assume entrepreneurial responsibility with us. Do you appreciate the spirit of a growing international company with Swiss roots and a strong corporate culture?

Then we look forward to receiving your online application at

What You’ll Do

• AI Solution Development
  • Conduct exploratory data analysis to extract insights and patterns that inform AI model design and development
  • Perform data cleaning, validation, and transformation (feature engineering) required by AI models
  • Design, develop, and evaluate AI models to address specific business needs
• AI Deployment and Operations
  • Deploy AI models into production environments, ensuring scalability, reliability, and performance
  • Implement and maintain model monitoring systems to track performance metrics and identify when models require retraining or adjustment.
  • Maintain reusable central feature store for AI model training and deployment
  • Implement automated pipelines for model training, validation, and deployment, adopting fit-for-purpose industry practices
• Stakeholder Engagement
  • Collaborate with cross-functional teams (e.g. data engineers, IT consultants, business users) to achieve project outcome
  • Present outputs from business analyses to HPB stakeholders, to translate data-driven insights into programme design and delivery

• Minimum 3 years of working experience in data science or developing AI/ML, including experience wrangling data in cloud-based analytics platforms and tools (e.g. Microsoft Azure, Databricks, Spark Ecosystems)
• Must be proficient in Python and possess adeptness with large-scale datasets.
• Bachelor / Master / PhD in Analytics, AI / Data Science, Computer Science, Engineering or Information Systems with major / project experience in data science and/or business analytics from a recognised university.
• o Professional certifications in business analytics / data science / ML engineering from accredited professional bodies coupled with a few years of related working experience for graduates from other disciplines, are also acceptable for the position
• Adaptive in a fast-paced matrix environment, overseeing multiple projects concurrently within an agile environment
• Possesses strong problem resolution, attention to detail and effective communication skills to manage and deliver complex projects involving internal and external stakeholders