Synthetic Data Specialist

5 days ago

Singapore beBeeDataScientist Full time
Data Scientist Job Description

We are seeking an experienced Data Scientist (Senior) to join our team.

The ideal candidate will have a strong background in machine learning frameworks, generative modeling, and privacy-enhancing techniques. They will be responsible for designing and operationalizing end-to-end synthetic data pipelines, implementing privacy-by-design techniques, and delivering hands-on workshops and training for client teams.

  • Key Responsibilities:
    • Embed briefly onsite with the client's data science, risk, or compliance teams to gather requirements, map data sources, and align on use cases.
    • Design and operationalize end-to-end synthetic data pipelines for client datasets from ingestion, training, generation to evaluation.
    • Implement privacy-by-design techniques (differential privacy, k-anonymity) and ensure compliance with privacy regulations (GDPR, CCPA, PDPA).
    • Deliver hands-on workshops and training for client teams on integrating synthetic data into their analytics and ML workflows.
    • Manage client engagements , ensuring deliverables, timelines, and satisfaction metrics are met.
    • Drive adoption of synthetic data methodologies by showcasing benchmark successes and business impact.

Benchmarking & Model Evaluation

  • Apply and benchmark synthetic data generators on public datasets.
  • Develop evaluation frameworks and dashboards to measure fidelity, utility, privacy risk and downstream task performance across multiple benchmarks.
  • Iterate on model selection and configuration , fine-tuning generators (GANs, VAEs, diffusion) and pipelines to maximize performance on both client data and open challenges.
Required Skills and Qualifications
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, Software Engineering, Data Science or a related quantitative discipline.
  • 5+ years in data science or analytics roles, with at least 2 years embedded in client environments or professional services.
  • Experience with machine learning frameworks (PyTorch, DP-SGD) for privacy-preserving ML applications
  • Deep knowledge of generative modelling (GANs, VAEs, diffusion) and privacy-enhancing techniques.
  • Strong domain familiarity with financial datasets (transactional, risk, regulatory).
Benefits
  • Flexible time-off arrangements
  • Flexible work arrangements - work from office or WFH on some days
  • Equity eligibility: Competitive equity packages, with grant size evaluated based on the candidate's experience, skills, and impact.
How to Apply
  • Please submit your application here.

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