Senior Director, Data Science and Analytics in Whitehall

You will lead and scale Preply's product, business, and marketing analytics and data science organization. Your mission is to turn rigorous experimentation and causal analysis into repeatable decision levers that improve retention, conversion, monetization, and LTV. This is a senior strategic role: you will set the vision, embed statistical expertise into product squads, run centralized metric governance and experiment tooling, own marketing measurement and optimization, and lead business analytics. You must be strongly technical, able to evaluate and approve technical designs, introduce higher standards, and raise the team's technical and methodological bar. You will partner closely with Analytics Engineering and Experimentation Platform to ensure correct instrumentation, trusted datasets, and a single source of truth. This role does not lead ML or Applied AI, which are separate functions.

Responsibilities

• Set strategy and roadmap for product analytics, business analytics, and marketing measurement.
• Build and lead a multidisciplinary team of product, marketing, and business analysts plus experiment and statistics leaders.
• Own the end‑to‑end experimentation practice: hypothesis, design, instrumentation, monitoring, analysis, and rollout.
• Lead marketing measurement and optimization: attribution, incrementality and holdout tests, media mix, cohort LTV, CAC and ROAS frameworks, and campaign experiments.
• Own business analytics and reporting: forecasting, finance partnership, board‑level metrics, and planning and performance reviews.
• Deliver and govern a single metrics layer, production BI marts/APIs, experiment tracking, and reproducible analysis pipelines.
• Define and enforce statistical standards and best practices across squads.
• Translate statistical findings into clear product and commercial priorities and ensure analyses drive measurable KPI improvements.
• Partner with Analytics Engineering and Data Platform to secure correct instrumentation, data lineage, and availability of SSOT datasets; insist on engineering and delivery improvements where needed.
• Act as the organization's technical judge for analytics and experimentation: review complex analyses, approve methodological approaches, and mandate improvements.
• Hire, mentor, and develop senior managers and leaders; run calibration, promotion, and succession planning.
• Represent analytics and experimentation at executive forums and drive cross‑functional alignment.

Qualifications

• Ideal candidate has experience and led product, marketing and business analytics. Must at least product and one of the other two.
• 12+ years in analytics or data science and 7+ years leading and scaling analytics or experimentation organizations, including managing managers and owning hiring, promotions, and org design.
• Documented track record of delivering measurable business outcomes through analytics and experimentation (retention, conversion, LTV, CAC, ROAS).
• World‑class experimentation and causal judgment: experiment design, power analysis, stopping rules, multiple‑testing correction, heterogeneity and uplift/holdout design, and interpretation of complex results.
• Deep marketing measurement experience: attribution, incrementality, holdouts, media mix modeling, cohort LTV, CAC/ROAS, and channel experimentation tied to budget decisions.
• Experience leading business analytics and reporting teams that partner tightly with Finance on forecasting and board‑level metrics.
• Proven partnership with Analytics Engineering or Data Platform to secure instrumentation, trusted datasets, lineage, and data quality; able to push for engineering improvements without owning the function.
• Technical leadership, ability to review and raise the bar for technical designs and build platforms at the design/review level.
• Demonstrated ability to raise the bar: instituting review processes, enforcing methodological and engineering standards, and improving team craft.
• Strong stakeholder partnership and executive presence: able to embed analytics into product and commercial teams and influence senior product, engineering, finance and commercial leaders.
• Operational rigor: experience setting metric governance, experiment tracking, automated analysis, and reproducible workflows across many squads.
• Advanced quantitative training preferred: MSc/PhD in a quantitative field preferred, or equivalent senior technical leadership.

Benefits

• An open, collaborative, dynamic and diverse culture.
• A generous monthly allowance for lessons on Preply.com.
• Learning & Development budget and time off for your self‑development.
• A competitive financial package with equity, leave allowance and health insurance.
• Access to free mental health support platforms.
• The opportunity to unlock the potential of learners and tutors through learning and teaching in 175 countries (and counting!).