Data Scientist

Space Executive; Singapore; On-site; SGD 75,000 - 100,000; Full time

Job summary

A leading recruitment agency is seeking a data scientist in Singapore to join a mission-driven organisation focused on privacy-preserving data solutions. You will be responsible for model development, feature and product development, and collaboration with engineering teams. Ideal candidates will have a Bachelor's degree and at least 3 years of experience in machine learning and data science, with a strong proficiency in Python and common ML frameworks. Apply to contribute to innovative data technologies.

Benefits

Work on cutting-edge privacy and data technologies

Collaborate with engineers and scientists

Be part of a mission-driven organisation

Qualifications

• Minimum of 3 years of hands-on experience in data science or machine learning.
• Strong foundation in ML concepts and model experimentation.
• Ability to bridge technical and non-technical communication.

Responsibilities

• Design and run experiments to evaluate SDG models.
• Develop product features related to ML/DS capabilities.
• Diagnose and resolve model training and performance issues.

Skills

Machine Learning

Python

Data Science

Model Experimentation

Collaboration

Education

Bachelor’s degree or higher in Computer Science, Data Science, or related field

Tools

PyTorch

TensorFlow

scikit-learn

FastAPI

Flask

Job description

About the role

We’re looking for a data scientist who’s equally passionate about machine learning research and software engineering to join our client’s privacy and synthetic data team.

Their mission is to build privacy-preserving data solutions that empower organisations to safely use and share data. One of their flagship products enables synthetic data generation (SDG) — a cutting‑edge privacy technology that allows users to generate realistic, privacy‑safe datasets for analytics and AI applications.

This cutting‑edge application is in a rapid growth phase with exciting new features in the pipeline, including API integrations and scalable model enhancements. You’ll play a key role in advancing their machine learning engine and integrating it into production‑ready systems used nationwide.

What You’ll Do

1. Model Development

• Design and run experiments to evaluate emerging SDG models (e.g. DDPM, ARF, Gaussian Copula).
• Investigate model performance across data types, sizes, and distributions.
• Tune hyperparameters, refine architectures, and propose new modeling approaches.

2. Feature & Product Development

• Collaborate with engineers to develop product features that rely on ML/DS capabilities (e.g. imputation, data constraints, preprocessing).
• Prototype and implement strategies for constraints handling, imputation, and privacy metrics.

3. Diagnostics & Debugging

• Work with users and engineers to diagnose and resolve model training issues, data integration challenges, and performance bottlenecks.
• Translate technical insights into clear, actionable solutions.

4. Documentation & Knowledge Sharing

• Create clear, user‑friendly documentation explaining model choices, metrics, and tuning parameters.
• Communicate complex ML and privacy concepts to non‑technical stakeholders.

5. Collaboration

• Partner closely with backend engineers (FastAPI, AWS) and frontend teams (Next.js/React) to integrate ML components into scalable systems.
• Participate in Agile ceremonies, code reviews, and technical design discussions.

Qualifications

• You should have a Bachelor’s degree or higher in Computer Science, Data Science, Business Analytics, or a related field.
• A minimum of 3 years of hands‑on experience in data science, machine learning, or applied research.
• You should have a strong foundation in ML concepts and model experimentation, along with a high level of proficiency in Python and common ML frameworks (PyTorch, TensorFlow, scikit‑learn).
• Any experiences in diagnosing training issues and improving model performance and building and deploying ML systems via REST APIs (FastAPI, Flask, etc.) will be highly regarded.
• The ability to read, synthesise, and apply emerging research to real‑world prototypes is crucial too.
• Understanding of Git, CI/CD, and collaborative software practices, and AWS or any other cloud environments will be important.
• You should be atrong communicator who can bridge technical and non‑technical worlds, as well as collaborative and comfortable in a fast‑paced Agile environment.

What’s in it for you?

• Work on cutting‑edge privacy and data technologies with real‑world impact.
• Collaborate with a team of engineers and scientists building innovative, large‑scale data systems.
• Be part of a mission‑driven organisation committed to ethical AI and responsible data use.

Interested?

Apply now and help shape the future of privacy‑preserving data science.