We are seeking a Data Scientist to:
- Conduct rigorous research and experimentation on emerging privacy-enhancing technologies,
- Design scalable, practical workflows suitable for government agency implementation, and
- Develop comprehensive frameworks and guidelines to support the successful deployment of PETs.
Job Scope
You will be involved in:
- Applied Research & Development a. Design and execute rigorous experiments to evaluate emerging PETs and solutions
- Develop proof-of-concepts that demonstrate real-world applicability and measurable impact
- Stay current with academic research and translate findings into practical, deployable solutions
- Contribute to the broader community through publications and knowledge sharing with government and international partners
Agency Partnership & Pilot Implementation
- Collaborate directly with agencies to deeply understand their unique privacy challenges and operational constraints
- Design and execute pilot programmes to test PET solutions
- Systematically gather user feedback and iterate on solutions based on practical deployment experiences and lessons learned
- Provide ongoing technical consultation and hands-on support to agencies throughout their privacy technology adoption journey
End-to-End Solution Innovation & Development
- Identify opportunities where PETs can address current common data challenges across government
- Architect and develop scalable solutions designed for widespread adoption across the ecosystem
- Establish clear implementation pathways and adoption frameworks for new privacy technologies
Cross-Functional Collaboration
- Work as a collaborative team player alongside data scientists, data engineers, software engineers, and product managers
- Partner strategically with agencies to align technical solutions with the evolving landscape of regulatory requirements and governance frameworks
Requirements
- Bachelors degree or higher in Computer Science, Data Science, Business Analytics or a related field, with 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 extensive experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
- Ability to analyze model behavior, diagnose training issues, and design experiments to optimise performance and reliability
Applied Research & Experimentation
- Demonstrated ability to read, synthesise, and critically evaluate academic research papers and technical literature
- Experience designing and conducting rigorous experiments to validate hypotheses and measure solution effectiveness
- Comfort working with ambiguous problems and developing novel approaches to complex challenges
Nice-to-Haves
- Experience with privacy-enhancing technologies, including but not limited to anonymisation, synthetic data generation or differential privacy.
- Familiarity with frontend integration workflows (Next.js/React).
- Prior experience working in multi-disciplinary teams.
