Senior Manager of Data Science

Join our team as a Senior Manager of Data Science, where you will help establish and shape the UK team, operate as a single function with the US-based data science organization, prioritize competing requests from various departments, and set the technical standards for your team. You will also take accountability for the delivery of your team's projects and have the opportunity to work remotely from anywhere in the US.

• Help shape the working norms, technical culture, and onboarding experience for the data scientists who join the UK team.
• Operate the UK team as a single function with the US-based data science organization, keeping standards, context, and priorities consistent.
• Partner with the Director of Data Science and the US team to prioritize competing requests from various departments into a shared roadmap.

• Prioritization Under Constraint: Demonstrated ability to help sequence a roadmap across competing stakeholder demands with limited headcount, and to make a clear, well-reasoned case for tradeoffs even when the final call is shared with others
• Engineering Rigor: Familiarity with production ML systems (cloud environments, CI/CD, ML Ops) sufficient to hold your team to a real production bar, not just notebook-quality work
• Executive Communication: Comfortable translating technical work into a narrative for senior leadership and non-technical stakeholders, and negotiating scope and timeline with them directly
• Education: BS, MS, or PhD in a quantitative field (Statistics, Mathematics, Economics, Physics, Operations Research, etc.) or equivalent experience. We weigh hands-on empirical research experience, such as a thesis or lab-based program, over the specific field of study
• Proven People Leadership: Track record of developing and retaining data science talent, including calibrating performance and managing through periods of team growth
• Distributed/International Collaboration: Experience working on or leading a team split across countries or significant time zones, comfortable with the communication overhead and async workflows that requires
• Technical Credibility: Strong enough in Python, SQL, and applied ML (regression/classification, time-series, causal methods) to review your team's technical decisions and unblock them, even without writing production code daily
• 8+ years of experience in Data Science or ML Engineering, including 2+ years directly managing data scientists or ML engineers
• Early-Stage Team Experience: Track record of joining or helping shape a brand-new team, office, or region from an early stage, rather than only working within an established structure
• US/UK Collaboration, Specifically: Direct experience working across a US/UK (or similar transatlantic) split team, ideally within a company still establishing its presence in one of those regions
• Advanced Business ML (experience leading or reviewing work in 1-2 of the following):
• Customer Behavior & Propensity Modeling: churn, propensity-to-buy, lead scoring, or lifetime value (LTV) models used to drive targeted marketing and product interventions
• Applied Forecasting: time-series forecasting, anomaly detection, or demand/revenue planning under limited historical data
• Optimization: marketing spend, inventory, or resource allocation engines
• Marketing Measurement: marketing mix modeling, multi-touch attribution, or incrementality testing to measure media effectiveness and inform budget allocation across channels
• Industry Experience: healthcare, DTC/subscription, or pharma background is a plus, not a requirement