Data Scientist

Overview

I’m working with a global digital consultancy that urgently needs a Data Science Lead to drive advanced statistical modelling, experimentation strategies, and causal analysis across major brand portfolios. This is a senior, hands-on role working in a fast-paced, highly collaborative environment.

What you’ll be doing

• Design, implement, and analyse causal inference experiments, including natural experiments and quasi-experimental methods
• Develop and apply conformal prediction frameworks to provide reliable uncertainty estimates for machine learning models
• Identify and control for confounding variables in observational studies
• Create robust statistical methodologies for causal effect estimation
• Collaborate with cross-functional teams to translate business questions into rigorous experimental designs
• Present technical findings to stakeholders in clear, actionable terms

What we’re looking for

• Advanced degree (MS or PhD) in a quantitative discipline with deep understanding of statistics
• 3+ years of professional experience applying statistical methods to real-world data
• Demonstrated expertise in experimental design, including randomized controlled trials and observational study methodologies
• Strong understanding of conformal prediction theory and applications
• Proficiency in programming languages such as Python or R, and relevant statistical packages
• Experience with causal inference frameworks (e.g., potential outcomes, causal graphs, do-calculus)
• Knowledge of modern machine learning techniques and how they intersect with causal reasoning
• Excellent communication skills, with the ability to explain complex statistical concepts to non-technical audiences
• Agency or client-service experience is highly desirable — familiarity with fast-moving campaigns and cross-functional collaboration is a big plus

Preferred skills

• Experience with heterogeneous treatment effect estimation
• Familiarity with Bayesian methods for causal inference
• Background in epidemiology is a plus
• Experience working with a causal inference ecosystem (e.g., PyWhy, CausalImpact, Synth, GeoLift)

Contract length: 2 months initially

Working pattern: Hybrid / remote (approx. 2–3 days onsite in London)

If this sounds like you, drop me a DM or email your CV to zoe.hinkinson@propellondon.com

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