Data Scientist/ Analyst (ML | Tensorflow | PyTorch | Public Sector)

BGC GROUP PTE. LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading data science firm is seeking a Data Scientist for the public sector in Punggol, Singapore. The candidate will be responsible for designing experiments, collaborating with engineering teams on product features, and developing machine learning models. A Bachelor's degree and 2-3 years of professional experience are required, alongside strong programming skills in Python and familiarity with AWS. The role offers a monthly salary of 7000-8000 SGD and a 12-month contract.

Qualifications

• At least 2-3 years of relevant professional experience.
• Experience in model development and experimentation.
• Ability to debug software-level issues affecting ML workflows.

Responsibilities

• Design and conduct experiments to evaluate models.
• Collaborate with teams to build product features requiring ML input.
• Write user-facing documentation pages.

Skills

Machine learning foundations

Programming proficiency in Python

Experience with ML frameworks (e.g. PyTorch)

Strong analytical skills

Team collaboration

Education

Bachelor’s degree in Computer Science or related field

Tools

AWS

Git

FastAPI

Job description

Job Title: Data Scientist (Public Sector)

Duration: 12 months

Location: Punggol

Salary: 7000-8000

Work Timing: 8.30am – 6.00pm (Monday to Thursday), 8.30am - 5.30pm (Friday)

Eligibility: Only Singaporeans

Main Responsibilities:

• 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, 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).
• Ability to analyze model behavior, diagnose training issues, and design experiments to improve performance.
• Familiarity with reading, synthesizing, 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.

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.

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.