Product Intelligence Data Scientist

AVEVA is creating software trusted by over 90% of leading industrial companies. We are looking for a Product Intelligence Data Scientist to build a unified intelligence layer that transforms raw usage signals, behavioral data, and lifecycle events into predictive, prescriptive insights - enabling teams to act on what the product is telling us, not just what gets reported. You will own the analytical models and frameworks that connect product behavior to business outcomes across acquisition, activation, adoption, expansion, and renewal.

• Partner with Product to define and validate hypotheses around feature adoption, friction points, and growth levers using experimentation methods
• Translate complex product signals into lifecycle intelligence that drives prioritization - surfacing what to build, fix, or sunset
• Build and own predictive models that quantify adoption maturity, churn risk, expansion propensity, and feature-market fit from product telemetry
• Design behavioral segmentation and cohort frameworks that reveal how users derive value - and where they don’t
• Develop causal and inferential analyses that connect product interactions to revenue outcomes (NRR, LTV, expansion)
• Create automated scoring systems (product-qualified leads, customer health, engagement intensity) that feed into GTM, Customer Success, and in-product workflows
• Build early-warning detection models that identify at-risk accounts from behavioral shifts before lagging indicators appear
• Communicate findings to senior leadership as clear, actionable business narratives, and democratise intelligence findings for the wider team

• 5+ years in data science or advanced analytics - ideally in a hybrid PLG/sales-led SaaS environment
• Strong Python and SQL; experience with data modelling and pipeline tools (dbt, Airflow, Dagster)
• Deep expertise in predictive modelling, causal inference, survival analysis, and experimentation (A/B, diff-in-diff, instrumental variables)
• Experience working directly with product telemetry and event-stream data at scale
• Solid understanding of SaaS lifecycle mechanics (ARR, NRR, LTV, PQLs, activation funnels)
• Ability to translate statistical findings into product and commercial strategy for non-technical stakeholders
• Degree in a quantitative discipline (Statistics, Computer Science, Mathematics, Physics, Economics, or equivalent)

• Master’s or PhD in a quantitative field
• Cloud data platforms (Snowflake, Databricks, Big Query, or Azure Synapse)
• Product analytics instrumentation experience (Amplitude, Mixpanel, Pendo, or custom event pipelines)
• MLOps - model deployment, monitoring, and retraining in production
• Experience building propensity or scoring models that integrate into CRM/CS platforms
• Familiarity with industrial software or enterprise SaaS contexts UK

• Flexible benefits fund, emergency leave days, adoption leave, 28 days annual leave (plus bank holidays), pension, life cover, private medical insurance, parental leave, education assistance program.
• It’s possible we’re hiring for this position in multiple countries, in which case the above benefits apply to the primary location.
• Specific benefits vary by country, but our packages are similarly comprehensive.

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We work in a hybrid way t roles are based at a local AVEVA office, with an expectation of being on-site 50% of your working hours to support collaboration and connection. Some positions are fully office-based depending on the nature of the work, and certain roles that support specific customers or markets may be remote. The working arrangement for this position will be confirmed during the hiring process.

AVEVA is committed to recruiting and retaining people with disabilities. Please let us know in advance if you need reasonable support during your application process. Find out more:

About AVEVA AVEVA is a global leader in industrial software with more than 6,500 employees in over 40 countries. Our cutting-edge solutions are used by thousands of enterprises to deliver the essentials of life - such as energy, infrastructure, chemicals, and minerals - safely, efficiently, and…