Data Analytics Lead

It all started with an idea in 2021. Initially built to democratize Bitcoin in France, Bitstack has gone from a simple product that invests spare change in bitcoin, to a crypto-native bank bringing a better way to save, spend, and grow money to our 300K+ users. We want to rebuild finance from the ground up to empower people to achieve financial freedom by participating in a more open and inclusive financial system. We’re a small, ambitious team of operators. We believe in moving fast, sweating the details, and creating products people truly love. At Bitstack, you’ll have the opportunity to shape not just our products, but the culture and practices of our entire organization. Bitstack is backed by YC, leading VCs like 13books Capital, Stillmark, Serena, and many more. We are building a product our users love and we are just getting started!

We’re hiring a Founding Data Scientist to build Bitstack’s data function from zero to one. You will own analytics engineering, measurement, and modeling, and you will help every team make faster, higher-quality decisions with trustworthy data.

This is a builder role for someone excited by greenfield work: defining the metrics that matter, setting up self-serve discovery, and delivering deep analyses and models that directly shape product, risk, and growth.

• Create a trusted “source of truth”

  Establish canonical metric definitions and datasets that leadership and teams rely on for decisions.

• Make data discoverable and self-serve

  Set up data discovery, documentation, and curated datasets so most questions do not require ad-hoc help.

• Improve decision-making velocity and quality

  Enable teams to move from “opinions” to “evidence” by making analysis repeatable, reviewable, and fast.

• Build product + business measurement

  Instrument core user journeys end-to-end, define funnels and cohorts, and ensure we can attribute impact to product launches.

• Deliver high-leverage insights and recommendations

  Own deep dives into activation, retention, pricing, fraud/financial crime, customer support drivers, and operational performance.

• Introduce experimentation and causal thinking

  Establish an experimentation framework where appropriate, and raise the bar on hypothesis-driven decisions.

• Add modeling where it matters

  Build pragmatic models (forecasting, segmentation, anomaly detection, propensity, risk scoring support) that drive measurable outcomes.
  

• Use quantitative analysis to understand what drives Bitstack’s business and product performance.

• Build full-cycle analytics work: datasets, dashboards, and executive-ready narratives.

• Create repeatable analytical frameworks (cohorts, segmentation, measurement plans) rather than one-off answers.

• Partner with Engineering to implement, validate, and monitor event logging and data quality.

• Work cross-functionally with Product, Engineering, Compliance/Risk, Ops, Support, and Finance to scope ambiguous problems and turn them into data-backed decisions.

• Proactively identify levers to move key metrics, size opportunities, and recommend actions.
  

• Strong quantitative foundation in Statistics, Economics, Math, CS, Physics, or equivalent practical experience.

• Expert SQL and comfort working directly with production-grade datasets.

• Strong Python (or R) for analysis, modeling, and automation.

• Experience with experimentation, hypothesis testing, and causal thinking (A/B testing, quasi-experiments when A/B is not feasible).

• Experience with analytical methods such as:

  • Funnel analysis and product measurement

  • Cohort retention, segmentation, and lifecycle analysis

  • Time-series analysis and forecasting

  • Regression / classification, model evaluation, and pragmatic deployment patterns

• Proven ability to take ambiguous problems and solve them in a structured, hypothesis-driven way.

• Strong stakeholder communication: you can turn messy analysis into clear recommendations and trade-offs.
  

• Analytical DB / warehouse experience (ClickHouse strongly valued, or similar).

• BI tools (Metabase, Looker, Tableau).

• Analytics engineering tooling (dbt).

• Product analytics tools (Amplitude, Mixpanel, PostHog).

• Data quality / observability practices (tests, monitoring, lineage/docs).
  

• You will build the foundations, not inherit them.

• You will be judged on impact and leverage, not ticket throughput.

• You will operate across analytics engineering + analytics + modeling, picking the right tool for the problem.
  

1. Intro call (45 min): background + what you want in a founding role.

2. Analytics & measurement deep dive (60 min): how you’d define metrics, instrumentation, and a decision framework for a Bitstack problem.

3. Take-home (or live) case + review (60 min): SQL + analysis + recommendation quality.

4. Behavioral / collaboration (60 min): stakeholder management, prioritization, and how you operate in ambiguity.

🌎 Work from our office in Paris (Bourse) or Remote

🕑 Flexible working hours

👩‍⚕️ One of the best health insurance plans with 100% employer contributions

🏄 Monthly team activities and bi-annual offsites

🍉 Swile meal vouchers

🤑 Competitive salary based on experience & Bitstack stock options

We hire talented and passionate people from all kinds of backgrounds, we don’t care about your age or where you studied. If you’re excited about the role but your past experience doesn’t match every bullet point in the job description, we still encourage you to apply. What matters most is that you’re a builder at heart, you share our values, and you’re enthusiastic about our mission.
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