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AVEVA

Industrial software for SaaS asset management

Product Intelligence Data Scientist

Data ScienceUpdated on Nov 6
Full-timeNo salary listed

About the Job

Requirements

  • At least 5 years in data science or advanced analytics, with experience in a hybrid product-led growth and sales-led SaaS environment.
  • Strong Python and SQL skills, and experience with data modelling and pipeline tools such as dbt, Airflow, or Dagster.
  • Expertise in predictive modelling, causal inference, survival analysis, and experimentation methods including A/B testing, difference-in-differences, and instrumental variables.
  • Experience working directly with product telemetry and event-stream data at scale.
  • Understanding of SaaS lifecycle mechanics, including ARR, NRR, LTV, PQLs, and activation funnels.
  • Ability to translate statistical findings into product and commercial strategy for non-technical stakeholders.
  • A degree in a quantitative discipline such as Statistics, Computer Science, Mathematics, Physics, or Economics, or equivalent.

Responsibilities

  • Partner with Product to define and validate hypotheses about feature adoption, friction points, and growth levers using experimentation methods.
  • Translate complex product signals into lifecycle intelligence that informs prioritization, including 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.
  • Develop behavioral segmentation and cohort frameworks to reveal how users derive value and where they do not.
  • Develop causal and inferential analyses linking product interactions to revenue outcomes, including NRR, LTV, and expansion.
  • Create automated scoring systems for product-qualified leads, customer health, and engagement intensity to feed into go-to-market, Customer Success, and in-product workflows.
  • Build early-warning detection models that identify at-risk accounts based on behavioral shifts before lagging indicators appear.
  • Communicate findings to senior leadership as actionable business narratives and make intelligence findings accessible to the wider team.

Desired Qualifications

  • A Master's or PhD in a quantitative field.
  • Experience with cloud data platforms such as Snowflake, Databricks, BigQuery, or Azure Synapse.
  • Product analytics instrumentation experience with Amplitude, Mixpanel, Pendo, or custom event pipelines.
  • MLOps experience, including model deployment, monitoring, and retraining in production.
  • Experience building propensity or scoring models that integrate with CRM or Customer Success platforms.
  • Familiarity with industrial software or enterprise SaaS contexts.

About the Company

AVEVA

Industrial software for SaaS asset management

AVEVA provides industrial software that helps companies digitally transform their operations in manufacturing, energy, and infrastructure. Its offerings are delivered as a subscription-based service (SaaS) for engineering asset management, rather than traditional perpetual licenses. The core product, CONNECT, is an open industrial intelligence platform that runs in the cloud and can scale as a business grows; it works with or without Schneider Electric hardware, thanks to its hardware-agnostic design. Along with software, AVEVA offers online training to help clients adopt the new SaaS model. Compared with competitors, AVEVA differentiates itself by being hardware-agnostic, offering a cloud-first, subscription platform, and an open platform that supports scalable, cloud-based engineering asset management. The company aims to help customers digitally transform their operations, improve efficiency, and reach broader markets through flexible, cloud-based software solutions.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Cambridge, United Kingdom
Founded
1967

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