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Senior/Lead Data Scientist
Mention Me
- London, England, United Kingdom
- London, England, United Kingdom
Über
The opportunity Become one of the top contributors to bring the new product vision live. Work end to end across metric design, data and modeling, experimentation, and product integration.
What you’ll do
Build components of new products that turn real customer signals into timely actions and measurable outcomes allowing customers to amplify consumer voice for LLM visibility advantage. Partner across Product, Engineering, CS, and Commercial to make the human signal visible, actionable, and compounding in the product.
Establish experimentation and measurement foundations: design how we test, learn, and prove impact; embed sound statistical practice; and turn results into simple, trusted narratives that guide product and commercial decisions.
Productionize and scale thoughtfully: ship durable data and model workflows in collaboration with the engineering team, ensure quality and monitoring, and document decisions so the system is reliable, explainable, and easy to evolve.
What you’ll bring
Track record, typically 4+ years, in applied data science for product or marketing in consumer or SaaS
Continuous learning mindset: you stay current with generative AI advances, prototype with new models and frameworks, evaluate them critically, and translate useful innovations into practical product improvements. You share learnings and raise the bar for the team.
Hands‑on ML skills: feature engineering, propensity or uplift modeling, model evaluation, monitoring
Strong Python and SQL with the ability to move from notebooks to production code
Practical data engineering instincts: event schemas, batch jobs, orchestration, data quality guardrails
Clear communication that translates complexity into actionable narratives for non‑technical audiences
Bias for action and ownership in ambiguous, fast‑moving environments
Nice to have
LLM applications for agentic solutions
Graph modeling
Personalization: propensity/uplift modeling, bandits, causal inference
Libraries: scikit‑learn, XGBoost, LightGBM, CatBoost, CausalML, Keras, DoWhy
Experience with dbt, Airflow, Looker or Metabase, AWS services such as S3 and Lambda
Experience in designing and implementing model/metric endpoints as part of a platform ecosystem with clear contracts and SLOs (e.g., FastAPI/Flask, OpenAPI), deploying via AWS Lambda/API Gateway or containers
How we work
Hybrid with in‑person collaboration at our Vauxhall HQ and flexibility for focused work
Cross‑functional by default with close partnership across Product, Engineering, CS, and Commercial
Outcome‑driven with small releases, fast validation, and scaling what works
Benefits
Hybrid working
Private medical insurance with Vitality, including enhanced mental wellbeing support, dental and vision policies and a range of lifestyle benefits and great incentives
Life insurance
Two Celebration Days; additional time off for you to celebrate religious days, cultural events, birthdays, anniversaries, or any other significant day that’s important to you
Enhanced parental leave
25 days annual leave (plus public holidays), increasing over your time as a Mentioneer
Regular social events, from chocolate‑tasting and pottery‑making to poker nights and picnics
Up‑to‑date tech you’ll need (we love Macs)
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Sprachkenntnisse
- English
Hinweis für Nutzer
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