Product Intelligence Data Scientist

Join AVEVA as a Product Intelligence Data Scientist, where you will build a unified intelligence layer that transforms raw usage signals, behavioral data, and lifecycle events into predictive, prescriptive insights. You will own the analytical models and frameworks that connect product behavior to business outcomes, partner with Product to define and validate hypotheses, and communicate findings to senior leadership. Enjoy a range of benefits including 28 days of annual leave, hybrid working, parental leave, private healthcare, and professional development opportunities.

Cloud data platforms (Snowflake, Databricks, BigQuery, or Azure Synapse)

Responsibilities

• Construire une couche d'intelligence unifiée qui transforme les signaux d'utilisation bruts, les données comportementales et les événements de cycle de vie en informations prédictives et prescriptives.
• Posséder les modèles analytiques et les cadres qui relient le comportement du produit aux résultats commerciaux à travers l'acquisition, l'activation, l'adoption, l'expansion et le renouvellement.
• Collaborer avec l'équipe produit pour définir et valider des hypothèses concernant l'adoption des fonctionnalités, les points de friction et les leviers de croissance en utilisant des méthodes d'expérimentation.
• Strong Python and SQL; experience with data modelling and pipeline tools (dbt, Airflow, Dagster)

Requirements

• Degree in a quantitative discipline (Statistics, Computer Science, Mathematics, Physics, Economics, or equivalent)
• Ability to translate statistical findings into product and commercial strategy for non-technical stakeholders
• Solid understanding of SaaS lifecycle mechanics (ARR, NRR, LTV, PQLs, activation funnels)
• Deep expertise in predictive modelling, causal inference, survival analysis, and experimentation (A/B, diff-in-diff, instrumental variables)
• 5+ years in data science or advanced analytics — ideally in a hybrid PLG/sales-led SaaS environment
• Experience working directly with product telemetry and event-stream data at scale
• Product analytics instrumentation experience (Amplitude, Mixpanel, Pendo, or custom event pipelines)
• Master’s or PhD in a quantitative field
• MLOps — model deployment, monitoring, and retraining in production

Preferred

• Experience building propensity or scoring models that integrate into CRM/CS platforms
• Familiarity with industrial software or enterprise SaaS contexts