Data Analytics Lead

The Role

Bitstack is entering a new phase of growth and we’re hiring a Data Analytics Lead to build our data function from scratch. This role reports directly into our CTO and will define how data powers product, risk, and growth decisions across the company. 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.

What Success Looks Like

• Create a trusted “source of truth”
• Make data discoverable and self‑serve
• Improve decision‑making velocity and quality
• Build product + business measurement
• Deliver high‑leverage insights and recommendations
• Introduce experimentation and causal thinking
• Add modeling where it matters

What You’ll Be Doing

• 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.

What We’re Looking for

• 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.

Tech Stack (nice to have, not required)

• Analytical DB / warehouse experience (BigQuery 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).

What makes this role different

• You will build the foundations, not inherit them.
• You will be judged on impact and leverage, not ticket throughput.
• You’ll operate across analytics engineering, measurement, experimentation, and modeling, choosing the right level of sophistication for the problem instead of over‑engineering.

Perks & Benefits

• 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