Head of Data Science

Overview

In this role you lead the data science practice for Bain’s Growth AI Performance System, shaping production-grade statistical models that guide large enterprises. You will own methodological standards, tackle the toughest modelling challenges, and translate outputs into decision-ready insights for senior stakeholders. You’ll work within a blended product and case-team setup, balancing research depth with practical, auditable software delivery. This is a startup-like leadership role within a global advisory firm, offering broad impact and ownership over architecture and direction.

Pay / Benefits

• Generous paid time off
• Parental leave
• Paid holidays
• Fully vested 401(k) company contribution
• Premium medical, dental and vision coverage
• Life and long-term disability insurance

Responsibilities

• Set and own the statistical standard across modules, from problem framing to production handoff
• Personally lead the most difficult modelling problems, including non-standard likelihoods and identifiability assessments
• Implement models in Python with probabilistic programming frameworks and ensure reproducibility
• Design inference and validation standards (MCMC/VI diagnostics, posterior checks, calibration) prior to client delivery
• Build and maintain a cross-model reconciliation framework for heterogeneous models
• Drive methodological innovation in Bayesian, causal, time-series, and discrete choice methods
• Lead, mentor, and develop module-level Data Scientists; present to senior client stakeholders
• Oversee data input quality and establish standards for schemas and uncertainty measures

Key requirements

• PhD in statistics or equivalent quantitative field is desirable but not mandatory
• 3+ years of applied statistical modelling in commercial or product contexts
• Strong background in hierarchical Bayesian methods, time-series, experimental and quasi-experimental inference
• Proficiency in Python and probabilistic programming frameworks; ability to translate outputs to production-ready code
• Experience communicating complex methodology to senior business stakeholders under live challenge
• Familiarity with commercial data sources (media data, panel data, POS data, pricing data) and data pipelines

• Strong communication and storytelling for senior stakeholders
• Analytical honesty and ability to defend assumptions under live challenge
• Team leadership, mentorship, and collaboration across cross-functional teams
• Python
• Probabilistic programming frameworks (e.g., PyMC, Stan via Python)
• Bayesian inference (MCMC, VI)

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