Welcometothejungle
Data Analytics Lead
NEWParis (fully)Full-timeGlobal
š Seniorš Remote
ActivePosted within the last 30 days
Job Description
[AI-summarized by JobStash]
You will build the data function from scratch: define canonical metrics, datasets, and measurement plans, and make data discoverable and self-serve. You will instrument core user journeys, create dashboards and executive-ready narratives, run deep analyses and pragmatic models (forecasting, segmentation, anomaly detection, propensity and risk scoring), introduce experimentation and causal frameworks, and partner with Engineering and product stakeholders to validate data quality and turn analysis into clear recommendations.
Requirements
- āStrong quantitative foundation in statistics economics mathematics computer science or equivalent experience
- āExpert SQL and experience with production-grade datasets
- āStrong Python or R for analysis modeling and automation
- āExperience with experimentation hypothesis testing and causal thinking (A/B testing and quasi-experiments)
- āExperience with funnel analysis cohort retention segmentation time-series analysis forecasting regression and classification
- āProven ability to solve ambiguous problems in a structured hypothesis-driven way
- āStrong stakeholder communication and ability to translate analysis into recommendations
- āNice to have: BigQuery or similar analytical warehouse dbt Metabase Looker Tableau Amplitude Mixpanel PostHog and data quality/observability practices
Responsibilities
- āEstablish canonical metric definitions and trusted datasets
- āSet up data discovery, documentation, and curated self-serve datasets
- āInstrument core user journeys, define funnels and cohorts
- āPerform quantitative analysis to understand business and product performance
- āBuild datasets, dashboards, and executive-ready narratives
- āPartner with Engineering to implement validate and monitor event logging and data quality
- āDeliver pragmatic models such as forecasting segmentation anomaly detection propensity and risk scoring
- āIntroduce experimentation frameworks and causal inference practices
Benefits & Perks
- āWork from our office in Paris or Remote
- āFlexible working hours
- āHealth insurance with 100% employer contributions
- āMonthly team activities and bi-annual offsites
- āSwile meal vouchers
- āBitstack stock options
Tech Stack
segmentationPythonSQLfunnel analysisMetabaseAmplitudeexperimentationClassificationA/B testingtime seriesproject:Bitstack