Senior Data Scientist in London

This is a high-impact, high-ownership role where you’ll act as the foundational data partner, owning data integrity end-to-end — from raw event tracking through to product and commercial insights.
I\’m looking for someone who can untangle complexity, fix what’s broken at the source, and build analytical foundations which my client can trust.
If you thrive in ambiguity, enjoy getting opinionated about how metrics should work, and like partnering closely with engineers to make data reliable, this role is for you.
Role Responsibilities Partner with the Engineering team to audit, diagnose, and fix tracking across key product surfaces
Trace metrics from dashboard to source tables to raw event logs, identifying breakpoints and driving resolution
Document data lineage, assumptions, and known issues
Define best-practice tracking approaches and advocate for instrumentation improvements
Build Foundational Analytics
Rebuild core analytical views, including registration funnels, credit purchase & burn flows, and engagement metrics
Create reliable, self-serve dashboards for Product and Commercial teams to monitor performance and identify opportunities
Validate and refactor legacy dashboards into trusted, well-documented assets
Partner with Product to answer strategic questions through exploratory analysis
Design experiments around monetisation, retention, and UX
Collaborate closely with Product, Engineering, and Commercial stakeholders to translate business questions into data requirements
Skills / Experience required Minimum 5 years’ experience in a Data Science, Analytics Engineering, or a similar quantitative role
Deep SQL expertise and hands-on experience with data warehouses (preferably Snowflake) is absolutely essential
Proven experience diagnosing data quality issues and resolving them in partnership with Engineering
Strong experience building and maintaining dashboards and analytical views (e.g. Looker or similar)
Excellent product intuition – you are able to demonstrate your understanding around why metrics matter, not just how to calculate them
You will be comfortable operating in ambiguity and structuring unclear problems
You will possess excellent communication skills with both technical and non-technical stakeholders
If you have any experience with any of the following, it would be advantageous:
Experience with mobile app analytics and event instrumentation
A background in two-sided marketplaces
Experience with experimentation platforms and causal inference
Familiarity with DBT or similar transformation frameworks
Experience with Python for EDA, statistical analysis, or ad-hoc data work
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