Job Description

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

• 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.