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About the Role

Growth AI Performance System is Bain’s integrated suite of agentic decisioning tools giving large organizations always-on intelligence across their most important growth decisions. This role offers the analytical depth of a top-tier consultancy, the technical ambition of a product company, and the commercial stakes of both. You will lead the statistical and modelling practice behind the platform, working inside Bain’s persistent product team alongside Tech Leads, Full-stack Engineers, and AI Engineers.

Responsibilities

Set and own the statistical standard across all Growth AI Performance System modules.
Personally lead the hardest modelling problems where standard playbooks do not cleanly apply.
Implement correct, tested, and reproducible estimators in Python using probabilistic programming frameworks.
Design and enforce inference and validation standards across all modules.
Own how statistical outputs become structured, versioned data products for engineers and agentic workflows.
Build and maintain a cross-model reconciliation framework for heterogeneous models.
Drive methodological innovation across various statistical methods.
Model marketing mix and media ROI, including ad stock and saturation structures and incrementality calibration.
Model brand equity and consumer choice, including latent brand constructs and measurement error models.
Model pricing, promotional lift, and assortment, including promotional lift decomposition and elasticity estimation.
Stay current with domain data sources and their modelling implications.
Build and lead the data science practice, including hiring, mentoring, and developing Data Scientists.
Present methodology, outputs, and recommendations directly to senior client stakeholders.
Operate as the practice’s most credible analytical voice under live challenge.
Lead working sessions where assumptions are stress-tested, outputs are interpreted, and methodology is challenged.
Use client feedback as a systematic input to methodological development.
Work with Data Engineering and platform Data teams to ensure model inputs are correctly structured, validated, and representative of real commercial data.
Define data requirements standards across modules.
Own evaluation of data quality at the model input layer.

Requirements

3 or more years of applied statistical modelling experience in commercial, consulting-adjacent, or product environments.
Track record of building statistical models that real clients or products depend on.
Direct experience presenting statistical methodology and model outputs to senior business stakeholders and defending analytical choices under live challenge.
Experience working in agile, cross-functional teams where analytical outputs must survive contact with real-world data and decision timelines.
Experience mentoring or managing data scientists, or setting analytical direction for a small practice, is a strong advantage.
Dissertation, publications, or teaching and review experience in applied Bayesian inference, causal inference, econometrics, or marketing and pricing analytics is a strong advantage.
Direct experience with marketing mix modelling, brand measurement, or pricing and promotional elasticity in production or consulting contexts is a strong advantage.
Ability to derive models from first principles and implement them in Python with probabilistic programming frameworks.
Software discipline to produce code that engineers can maintain, test, and reproduce.
Fluency in inference diagnostics and model criticism.
Understanding of identifiability, partial identification, and parameter recovery.
Experience designing and running experiments and validation frameworks.
Ability to translate model outputs into structured, versioned analytical artefacts.
Familiarity with commercial data sources and their limitations.
Working knowledge of how model outputs integrate into product interfaces and agentic workflows.
Active use of AI-assisted coding tools to accelerate derivation, prototyping, and hypothesis testing.

Skills

Statistical modelling
Python
Probabilistic programming frameworks
Bayesian inference
Time-series methods
Hierarchical modelling
Causal inference
Quasi-experimental methods
Discrete choice modelling
Marketing mix modelling
Brand measurement
Pricing and promotional elasticity

Location

Chicago
London
Sao Paulo
Warsaw

Work Type

Permanent Full-Time

Experience Level

3 or more years of applied statistical modelling experience

Education Level

PhD in statistics or equivalent quantitative field with dissertation-level applied inference work is desired but not mandatory
Mathematics
Econometrics
Related quantitative field with a dissertation in applied inference

Salary/Compensations

In Illinois, the good-faith, reasonable annualized full-time salary range for this role is between $226,000 – $276,750
Annual discretionary performance bonus
This role may also be eligible for other elements of discretionary compensation
For all other locations, the good-faith, reasonable annualized full-time salary range for this role is commensurate with competitive geographic market rates

Benefits

4.5% 401(k) company contribution, which increases after 3 years of service and is 100% vested upon start date
Bain pays 100% individual employee premiums for medical, dental and vision programs
Generous paid time off, including parental leave, sick leave and paid holidays
Fully vested 401(k) company contribution
Paid Life and Long-Term Disability insurance

About the Company

We are proud to be consistently recognized as one of the world’s best places to work.
We are currently the top ranked consulting firm on Glassdoor’s Best Places to Work list and have earned the #1 overall spot a record seven times.
Extraordinary teams are at the heart of our business strategy.
We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.
Growth AI Performance System sits at a rare intersection few organizations can genuinely offer: the analytical depth and client access of a top-tier consultancy, the technical ambition of a product company, and the commercial stakes of both.
This is a startup inside an established company.
You get genuine early-stage ownership -- real influence over architecture and product direction -- backed by Bain’s global scale, client relationships, and leadership commitment.
The pace of a startup with the runway of a global firm.

Equal Opportunity

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.