Top Tech Jobs & Startup Jobs

Lead end-to-end technical recruiting across engineering, product, data, design, and research. Partner with hiring managers, source candidates, conduct interviews, manage offers, build talent pools, coach interviewers, monitor hiring metrics, and improve recruitment processes. The role also leads talent acquisition initiatives and recruitment campaigns while ensuring strong candidate and hiring manager experiences.

Build, calibrate, and scale Bayesian Media Mix Models and other econometric/time-series machine learning models for marketing measurement. Automate model validation and monitoring, productionize reproducible pipelines, and partner with decision scientists and marketing leadership to translate model outputs into business decisions.

Own end-to-end analyses to quantify business impact of frontend platform changes, define and track technical and behavioral metrics, design and analyze A/B tests, partner with engineering and design during discovery, and scale decision-science methodologies across the organization to inform strategic platform decisions.

Lead fraud-related analytics and decision science for payments: analyze large datasets, build and validate statistical/ML models, define KPIs, enable self-service dashboards, and partner cross-functionally to optimize fraud detection and payment product safety.

Own a product area within Marketplace, set vision and objectives, prioritise opportunities, run discovery and A/B tests, define requirements, manage roadmaps with Design, Engineering and Analytics, and deliver measurable improvements to user experience and revenue.

Own product vision and strategy for a marketplace area. Define objectives, prioritise opportunities, run discovery, scope solutions, collaborate with Design, Engineering, Analytics and Data Science, manage roadmaps, run A/B tests, and deliver high-quality, data-driven product outcomes that improve member experience and revenue.

Build, deploy, and scale Bayesian MMMs and econometric/time-series models to measure marketing impact. Engineer reproducible, production-grade model pipelines, automate validation and health monitoring, and translate model outputs into business decisions while partnering with marketing leadership.

Own data-driven fraud detection and prevention for payments: analyze large datasets, develop and validate statistical tests and KPIs, build dashboards, collaborate with product and engineering, and improve real-time ML predictors, rules, and external signals to protect transactions while minimizing friction for legitimate users.

Build, calibrate, and scale Bayesian MMMs, econometric and ML models to quantify marketing impact. Automate validation and monitoring, productionize reproducible pipelines, and translate model outputs into business decisions for marketing leadership.

Work on payments fraud detection by analyzing large datasets, building and evaluating statistical/ML predictors and business rules, running experiments, creating dashboards, monitoring KPIs, and collaborating with product and engineering to improve fraud prevention and payments safety.