Senior Data Scientist - ML, Decision Science & Impact

MVF; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Summer Fridays

25 days holiday + 8 bank holidays (r о

Hybrid working - 3 days in office

Life Assurance

Defined Contribution Pension

Be Well wellbeing program

Two charity days a year

Job summary

MVF is looking for a senior data scientist to advance classical ML and decision science across lead generation. You will build and monitor models for lead quality and traffic performance, frame business decisions, and work closely day-to-day with AI engineers, product managers and operators.

You will own model development, experiment design, and evidence-based handovers, while contributing to a culture of rigorous validation and measurable impact.

Qualifications

• 5+ years as a data scientist or in a similar applied ML role.
• Statistics and experimentation: hypothesis testing, A/B testing, power and sample sizing.
• Classical ML: classification and ranking with scikit-learn and XGBoost or LightGBM, validated rigorously.
• Decision science: contextual bandits, causal inference or uplift modelling.
• Strong Python and SQL, Git and code review.

Responsibilities

• Build models for lead quality and traffic performance; include classification, ranking, anomaly detection, and forecasting.
• Prove impact with KPIs and A/B tests; work with platform team on deployment.
• Frame decisions by turning business rules into actions, context, and reward.
• Learn policies with contextual bandits and off-policy evaluation; ensure safe live deployment.
• Collaborate with AI engineers, product managers and operators to ship robust analytics.

Skills

Python

SQL

Git

A/B testing

SageMaker

XGBoost/LightGBM

Tools

SageMaker

Open Bandit Pipeline

EconML

Snowflake

dbt

Job description

MVF is looking for a senior data scientist to advance classical ML and decision science across lead generation. You will build and monitor models for lead quality and traffic performance, frame business decisions, and work closely day-to-day with AI engineers, product managers and operators.

You will own model development, experiment design, and evidence-based handovers, while contributing to a culture of rigorous validation and measurable impact.