Responsibilities
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
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
Identify opportunities where PETs can address current common data challenges across agencies
Architect and develop scalable solutions designed for widespread adoption across the WOG ecosystem
Establish clear implementation pathways and adoption frameworks for new privacy technologies
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
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 extensive experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit‐learn).
Ability to analyze model behavior, diagnose training issues, and design experiments to optimize performance and reliability.
Demonstrated ability to read, synthesize, 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.
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 multidisciplinary teams.
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.
Strong in communication with the ability to explain complex technical concepts clearly to diverse audiences.
This is a 1-year Contract position under People Advantage (Certis Group).
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