Senior Product Data Scientist: Growth & Engagement

Mubi; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

MUBI is seeking a Senior Product Data Scientist to understand what drives engagement and retention, and to raise the bar for how we use data and experimentation to make product decisions.

This role sits at the intersection of product analytics and data science, embedded in the Engagement & Discovery squad and collaborating with product managers, engineers and designers as the data voice in a multidisciplinary team.

Qualifications

• 3–5 years in product analytics or data science for digital subscriptions.
• Strong grounding in statistics, experimentation and machine learning.
• Proficient in SQL and Python for analysis and modelling.
• Experience designing, running and interpreting experiments with statistical rigour.

Responsibilities

• Champion a culture of experimentation with frameworks, metrics and guardrails.
• Embed with a product delivery team to shape the roadmap with data and defined metrics.
• Propose analyses, models and experiments and present actionable recommendations to stakeholders.
• Investigate drivers of engagement, retention and lifecycle across viewing, curation and pricing.
• Develop churn and propensity models and LTV estimates to inform decisions.
• Leverage AI tools to accelerate analysis and modelling.

Skills

Data science methods

Statistics

Experimentation

Machine learning

Communication

Independent mindset

Detail-oriented

Education

Postgraduate qualification in data science or related quantitative field

Tools

SQL

Python

Claude Code

dbt

Snowflake

Omni BI tool

Job description

MUBI is seeking a Senior Product Data Scientist to understand what drives engagement and retention, and to raise the bar for how we use data and experimentation to make product decisions.

This role sits at the intersection of product analytics and data science, embedded in the Engagement & Discovery squad and collaborating with product managers, engineers and designers as the data voice in a multidisciplinary team.