Data Scientist (MRG)

User Experience Researchers Pte Ltd (Singapore); Singapore; On-site; SGD 50,000 - 70,000; Full time

Job summary

A data innovation consultancy in Singapore seeks a Data Scientist (MRG) to drive advancements in data science, applied machine learning, and software engineering. The role focuses on model experimentation, working closely with engineering teams to develop machine learning-powered features. Ideal candidates should have a Bachelor's degree and 2-3 years of relevant experience, strong proficiency in Python, and a solid understanding of machine learning concepts. This full-time position is geared towards entry-level talent excited to innovate in the data privacy space.

Qualifications

• 2-3 years of relevant professional experience.
• Strong foundation in machine learning with hands-on experience in model development.
• Working knowledge of backend development and cloud environments.

Responsibilities

• Design and conduct experiments to evaluate emerging SDG models.
• Collaborate with software engineers to build product features needing ML input.
• Diagnose user issues and provide actionable fixes.

Skills

Machine learning

Python programming

Model experimentation

Cloud environments (AWS)

Data analysis

Education

Bachelor’s degree or higher in Computer Science, Data Science, Business Analytics

Tools

PyTorch

TensorFlow

scikit-learn

FastAPI

Flask

Job description

About the Data Scientist (MRG) Role

Our team is searching for a Data Scientist (MRG) to innovate at the intersection of data science, applied machine learning, and software engineering. In this role, you’ll design and experiment with emerging generative models, refine architectures, and develop ML-powered product features in collaboration with engineering teams. This position offers the opportunity to shape production-ready systems that advance privacy and synthetic data technologies across government.

Key Responsibilities

• Model Development
  • 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
• Feature & Product Development
  • 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
• Diagnostics & Debugging
  • 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.
• Documentation & Knowledge Sharing
  • 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.
• Collaboration
  • Work closely with the SWE team (Next.js, FastAPI, AWS) to integrate the generation engine into production-ready systems.
  • Participate in Agile rituals, code reviews, and design discussions.

Requirements

• Bachelor’s degree or higher in Computer Science, Data Science, Business Analytics, or a related field.
• At least 2-3 years of relevant professional experience.
• Core Data Science & ML skillset
  • 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).
  • Ability to analyse model behavior, diagnose training issues, and design experiments to improve performance.
• Applied Research & Experimentation
  • Familiarity with reading, synthesising, and ability to translate emerging research into practical prototypes.
• Software Engineering
  • Working knowledge of backend development (REST APIs, FastAPI, Flask, or similar).
  • Comfortable working with cloud environments (AWS preferred).
  • Ability to debug and fix software-level issues when they affect ML workflows.
  • Familiarity with Git, CI/CD, and collaborative coding best practices.

Preferred Qualifications

• Experience with privacy-enhancing technologies, anonymisation, synthetic data generation or differential privacy.
• Familiarity with frontend integration workflows (Next.js/React).
• Prior experience working in multidisciplinary product teams.
• Curiosity and willingness to learn new domains (esp. data privacy).
• Strong communication skills to explain technical concepts to both engineers and non‑technical stakeholders.
• Inclination to work in a collaborative, fast‑moving Agile environment.

Job Details

• Seniority level: Entry level
• Employment type: Full‑time
• Job function: Engineering and Information Technology