Data Scientist (ML)

TL;DR

Data Scientist (ML): Building and deploying predictive engines for customer strategy with an accent on Churn Propensity, Next Best Action (NBA), and xLTV modeling. Focus on owning the end-to-end ML lifecycle from Proof of Concept to production-ready models.

Location: London, United Kingdom

Company

UW simplifies utilities by providing energy, broadband, mobile, and insurance services in one place.

What you will do

• Design and deploy ML models for Churn Propensity and Next Best Action (NBA) engines.
• Develop advanced Customer Segmentation using clustering techniques.
• Own xLTV and ROI logic to optimize acquisition and retention spend.
• Collaborate with Data Engineers to productionize scalable models and monitor drift.
• Design and analyze A/B tests to validate model effectiveness and measure commercial uplift.
• Translate complex statistical outputs into actionable insights for business stakeholders.

Requirements

• Proven Data Science experience within a retail, B2C subscription, or utilities environment.
• Strong ML knowledge in Regression, Classification, Clustering, and Time-series.
• Expert-level Python (pandas, scikit-learn) and advanced SQL.
• Ability to link technical metrics to business KPIs.
• Strong data storytelling skills to explain "black box" models to business leaders.

Culture & Benefits

• Annual discretionary performance bonus ranging from 15-40%.
• Optional four-day working week (90% pay for 90% impact).
• Flexible working and limited "work from anywhere" travel perk (up to 6 weeks per year).
• 25 days holiday plus bank holidays.
• Matched-contribution pension scheme and life assurance.
• Allowance for private health insurance, dental insurance, or gym membership.