Data Scientist (MRG)

User Experience Researchers Pte.Ltd; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

A data science and machine learning company in Singapore is seeking a professional to develop models, collaborate with software engineers, and communicate technical insights. The ideal candidate will have a Bachelor's degree in a relevant field along with programming proficiency in Python and experience with machine learning frameworks. This role offers opportunities in documentation, diagnostics, and collaboration within Agile teams.

Qualifications

• 2-3 years of relevant professional experience in Data Science or related field.
• Strong foundation in machine learning and model development.
• Hands-on experience with ML frameworks and Python.

Responsibilities

• Design and conduct experiments for SDG models.
• Collaborate with engineers on product feature development.
• Diagnose and fix user issues related to model performance.

Skills

Machine learning

Python programming

Problem diagnosis

Technical communication

Agile methodologies

Education

Bachelor's degree in Computer Science or related field

Tools

PyTorch

TensorFlow

scikit-learn

FastAPI

AWS

Job description

Job Scope:

This role will be at the intersection of data science, applied machine learning, and software engineering.

You will be involved in:

1. 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.

2. 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.

3. 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.

4. 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.

5. 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:

1. Bachelors degree or higher in Computer Science, Data Science, Business Analytics or related field, with at least 2-3 years of relevant professional experience.

2. 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 analyze model behavior, diagnose training issues, and design
  experiments to improve performance.

3. Applied Research & Experimentation

• Familiarity with reading, synthesizing, and ability to translate emerging research into practical prototypes

4. 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

5. Nice-to-Haves

• Experience with privacy-enhancing technologies, anonymisation, synthetic data generation or differential privacy.
• Familiarity with frontend integration workflows (Next.js/React).
  Prior experience working in multi-disciplinary product teams.

6. Mindset & Collaboration

• 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