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Data Scientist & Analytics Engineer

Ledger · Paris, France, France

💰 ca. 56 000–76 000 EUR/år (estimat · vanlig lønn, ikke bekreftet)HeltidFjernarbeid · EuropeDirekte fra arbeidsgiverFrist 2.12.2026

Søk på stillingenÅpne i Havn (lagre, sammenlign, KI-hjelp)

We’re a team of experts pushing the limits of what’s possible, united by our common goal to unlock true freedom through digital ownership, making technology accessible for all. We believe in a world where users, creators and enterprises manage their value with ownership and freedom. Our curiosity drives us to innovate, empowering individuals on a global scale. We believe change is constant and our team moves forward as one, with a culture of problem-solving where every employee is empowered and supported to challenge tradition and create solutions. Our mission is simple: to make self-custody accessible and give people the keys to their own financial futures. If you want to make a true impact, we want you to join us at Ledger. At Ledger, we’re proud to be the global platform for digital assets and Web3, with over 20% of the world’s crypto assets secured through our Ledger devices. With our headquarters in Paris, and offices in Vierzon, Grenoble, Montpellier, London, Portland, Geneva, Zurich and Central Singapore, we have a team of around 600 professionals developing a variety of products and services to enable individuals and companies to securely buy, store, swap, grow and manage crypto assets – including the Ledger hardware wallets line with more than 7.5 millions units already sold in 200 countries. The team: You'll join the Data Team, responsible for turning data into actionable insights and recommendations for our consumer sales and marketing operations across all channels. What you’ll be doing: - Own consumer sales analytics end to end: Ledger.com http://Ledger.com, Amazon, wholesale and resellers, from sell-in to sell-out, with one consistent view of revenue, units and margin - Measure the true incremental impact of pricing, promotions and marketing campaigns with rigorous causal methods and experiments, and turn the results into budget recommendations for the Growth team - Develop and improve data models (dbt/Snowflake) across varied data sources (sales, sell-out, marketing, web analytics) with the support of the data engineering team; co-own data quality alerting - Own performance marketing measurement (attribution, ROAS, CAC), reconciling ad platforms, GA4 and internal sales data into a single source of truth - Build and maintain Tableau dashboards that give business teams a clear, reliable view of their performance - Model customer value (LTV, repurchase behavior, services attach) and feed it back into marketing ROI decisions - Work as part of an AI-augmented team: use LLM-based workflows and AI agents daily to automate analyses and accelerate delivery - Create and deliver presentations that turn complex analyses into clear recommendations for stakeholders up to ExCom level What we’re looking for: - Proven hands-on data science experience applied to business decisions: you have run causal inference studies (CausalImpact, difference-in-differences, synthetic control, geo-experiments) and/or built predictive models (LTV, repurchase, propensity) whose results changed a budget or pricing decision - Strong statistical rigor: comfortable with experiment design, confidence intervals and power, and able to clearly say when a result shows no detectable effect - 2 to 4 years of experience in data analytics, analytics engineering or data science - Strong SQL - dbt skills are a plus - Tableau skills are a strong plus - Data driven and business oriented; able to challenge stakeholders' methodology - Familiarity with marketing/web analytics data: GA4, ad platforms (Google Ads, Amazon Ads), affiliation networks are a strong plus At Ledger, we are dedicated to continually investing in our employees which is why we offer more than just salaries; we provide comprehensive compensation packages that include a wide range of benefits. Here are some of the benefits you can look forward to: - Flexible work options - Our hybrid policy allows employees to work from home up to 3 times per w

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