Senior / Lead Data Scientist

• 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.

• 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, * 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

• 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
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Job Description Senior Data Scientists Hybrid working pattern Who we are - Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and...