Senior/Staff Applied Machine Learning Scientist

Role overview Senior/Staff Applied Machine Learning Scientist role on a data science team that builds and optimizes advanced ML algorithms powering advertising effectiveness and ROI at massive scale. The position owns end-to-end development of production-grade ML models, from prototyping to deployment, within a high-volume environment processing millions of requests and billions of decisions per day. Remote-first, open to candidates located anywhere in the UK.

Responsibilities - Lead the creation and optimization of advanced machine learning algorithms, from developing new methods to refining existing techniques, to enhance advertising effectiveness and ROI. - Own the end-to-end development of production-grade ML models, writing efficient and scalable code while collaborating with Data Engineers to deploy and integrate algorithms into live systems. - Drive the prototyping and rigorous testing of innovative algorithms and data pipelines using historical data to validate performance and scalability. - Lead iterative improvements based on data-driven insights.

Requirements - 3+ years of industry experience. - Master's degree or PhD in Computer Science, Statistics, Operations Research, or a related field; dual degrees a plus. - Ability to take an ambiguously defined task and break it down into actionable steps. - Comprehensive understanding of statistics, optimization, and machine learning. - Proficiency in coding, data structures, and algorithms. - Enjoyment of working in a friendly, collaborative environment with others.

Nice to have - Dual degrees combining quantitative and computational disciplines. - Experience deploying ML models into high-throughput, low-latency production systems.

Benefits and work setup - Remote-first position open to candidates located anywhere in the UK. - Base salary band of £102,656–£141,152 GBP. - Highly competitive compensation with retirement/pension savings, paid time off including a birthday off, mental health support, health benefits from day one, work-from-home reimbursements, optional WeWork membership, parental leave, training and onboarding, and learning budgets for conferences and courses.