Product Intelligence Data Scientist

AVEVA is creating software trusted by over 90% of leading industrial companies.

Job Title:

Product Intelligence Data Scientist

Location:

Cambridge/London, United Kingdom (Hybrid)

Employment Type:

full-time The Job 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.

Key Responsibilities 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’tDevelop 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 Essential Requirements5+ 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)
Desired Skills and Competencies 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 Benefits include:

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.

Find out more:  working

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…