Applied Science Manager, Marketplace Optimisation

Role overview Lead the scientific strategy for optimizing a two-sided research marketplace that connects organizations with a global pool of study participants. You will manage a team of four data and applied scientists, with scope to grow it, and partner with Product and Engineering to turn research and algorithms into production systems that improve study fulfilment, participant experience, and data quality.

Responsibilities - Set the direction for marketplace science and lead development of matching, ranking, allocation, and forecasting methods. - Optimize supply and demand to improve marketplace efficiency and study completion. - Use experiments, causal inference, simulations, and model evaluation to measure impact and guide decisions. - Work with Product and Engineering to turn marketplace challenges into scalable algorithms and influence product priorities. - Deploy models into production and assess their effects on the marketplace and its participants. - Coach and develop the team, set technical standards, and build its capabilities as it grows.

Requirements - Experience managing, coaching, and developing data scientists or applied scientists. - Strong applied machine learning, optimization, and algorithm development skills. - A track record of delivering production decision systems. - Solid knowledge of experimentation, causal inference, and rigorous model evaluation.

Nice to have - Experience with two-sided marketplaces or large-scale platforms.

Benefits and work setup - Remote work, competitive salary, and benefits. - Opportunity to shape marketplace strategy and algorithms in a growing team working on human-generated data for research and AI development.