Staff Data Scientist

Stack

Responsibilities

• ▹Develop a strategic understanding of the domain's value drivers (user behaviour, marketplace dynamics, pricing, long-term unit economics) and turn it into decision frameworks for leadership
• ▹Define the long-term measurement and experimentation strategy for the domain, identifying structural growth levers
• ▹Design the experimentation programme, run and evaluate large-scale experiments
• ▹Lead deep analytical investigations into customer behaviour and retention dynamics, reframing ambiguous business questions into structured analyses
• ▹Own impact modelling and scenario analysis for major product initiatives, supporting quarterly and annual planning through forecasting, trade-off analysis and risk assessment
• ▹Own the definition and governance of key metrics in the domain, aligned with company-level objectives
• ▹Act as a senior thought partner to product, engineering and data leaders and raise analytical standards across the organisation
• ▹Lead cross-domain analytical initiatives (e.g. company-wide LTV modelling, pricing strategy, marketplace health framework)

Requirements

• ▹Demonstrated track record of materially influencing product or business strategy in complex environments, with company-level impact
• ▹Expertise in experimentation and causal inference, including under imperfect conditions
• ▹Strong understanding of subscription and marketplace economics: LTV modelling, cohort dynamics, retention mechanics, pricing trade-offs
• ▹Strong technical proficiency (e.g. SQL, Python), able to review the analytical work of others, set coding standards and design scalable analytical workflows
• ▹Experience mentoring and technically guiding senior data scientists
• ▹Curiosity, problem-solving and critical-thinking skills, proactively identifying challenges
• ▹Ability to influence Directors and VP-level stakeholders and drive clarity in high-stakes strategic discussions
• ▹Interest in the bigger picture and in impacting the product roadmap and strategy

Nice to have

• ▹Background in two-sided marketplaces or digital businesses (B2C, B2B2C)
• ▹Experience with product analytics tools (e.g. Amplitude, Mixpanel, Heap)
• ▹Experience applying advanced analytical methods (forecasting, causal modelling, pricing optimisation)
• ▹Familiarity with data visualisation tools (e.g. Tableau, Looker, Power BI)
• ▹Master's degree or PhD in a quantitative field
• ▹Experience developing senior data scientists and raising the analytical bar

Soft skills

What we offer

• ▹Open, collaborative, dynamic and diverse culture
• ▹Generous monthly allowance for lessons on Preply.com, learning and development budget and time off for self-development
• ▹Competitive financial package with equity, leave allowance and health insurance
• ▹Access to free mental health support platforms

About the company

Preply creates human-led, tech-enabled learning experiences: 100,000+ tutors teach 90+ languages in 180 countries. The company is data-driven and runs hundreds of A/B tests to continually optimise its product.