Data Scientist

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Collaborate with Product and BI to transform business objectives into well-defined ML challenges that include clear success metrics and boundaries.

• Develop and deploy models for segmentation, churn prediction, lifetime value (LTV), and recommendations.

• Create evaluation frameworks that incorporate both offline benchmarks and online feedback mechanisms to guarantee models are accurately measured.

• Work in conjunction with Engineering on production design aspects such as latency, payload architecture, fallbacks, and failure scenarios.

• Track model performance over time, identify drift, and manage retraining and iteration processes.

• Utilize product telemetry and user feedback to foster ongoing enhancements of models and features.

• Collaborate with AI coding agents to expedite development while ensuring human oversight is maintained.

• Effectively communicate outcomes, trade-offs, and recommendations to both technical and non-technical teams.

⛳️ Requirements

• Over 5 years of experience as a Data Scientist, Applied Scientist, or ML Engineer.

• Proficient in SQL and Python with hands-on experience in production ML.

• Background in churn analysis, segmentation, LTV, or recommendation systems.

• Comfortable engaging with production systems and APIs.

• Familiarity with AI coding tools and agent-based workflows.

• Excellent communication skills, capable of simplifying complex technical ideas.

• Nice to Have: Experience in loyalty programs, CRM, or retail analytics; familiarity with LLM or AI agents; experience in developing internal tools or ML infrastructure; bilingual in French and English.

🏝️ Benefits

• Flexibility: A people-first approach that emphasizes outcomes rather than location or hours worked.

• Innovation: Engage at the crossroads of machine learning, product strategy, and AI-assisted development.

• Collaboration: Work closely with Product, Engineering, and BI in a dynamic, supportive environment.