Senior Manager, Data Science

Bain & Company • Boston, MA

3d • $164,500 - $206,500

About The Position

The Senior Manager, Data Science owns the statistical and analytical core of a Growth AI Performance System product module, designing, building, and validating models that power client-facing outputs across marketing ROI, brand strategy, or pricing and commercial analytics. The role is part of Bain’s standing product team and a blended product and case team, working under the Tech Lead and alongside Full-stack Engineers, Data Engineers, the platform Data team, and AI Engineering to turn model outputs into scalable, repeatable product features and agentic workflows.

The position applies Bayesian statistics, time-series forecasting, experiment design, and domain-specific analytical methods to complex commercial problems. Model outputs must be methodologically sound, production-ready, interpretable, and useful to both analytical peers and senior client stakeholders. Work includes marketing mix modeling, brand equity measurement, price elasticity, and promotional lift, with attention to client-specific data limitations and uncertainty.

The role connects analytical development to live commercial outcomes. Feedback from client engagements informs model improvements, and the Data Scientist presents methodology, defends assumptions, facilitates discussions, and adjusts models based on stakeholder feedback. The position also contributes to reusable analytical frameworks, model evaluation standards, data requirements, and responsible deployment practices.

Requirements

• At least 8 years of applied data science or quantitative modeling experience in a commercial, consulting-adjacent, or product environment.
• Deep Bayesian statistical expertise, including designing prior structures, diagnosing convergence issues, stress-testing assumptions, and defending inferences.
• Strong domain knowledge in at least one of marketing mix modeling and media ROI measurement, brand equity and consumer choice modeling, or pricing and revenue growth management analytics.
• Strong Python proficiency for statistical modeling and data analysis, including probabilistic programming, scientific computing, and disciplined model-code development suitable for engineering handoff.
• Experience designing and running experiments, including A/B testing, out-of-sample validation, back-testing, and sensitivity analysis, and interpreting results rigorously.
• Ability to translate model outputs into structured data products with clear schemas, documented uncertainty, and confidence bounds for engineers and agentic workflows.
• Familiarity with commercial analytics data sources such as media platform, panel, point-of-sale, pricing, and promotional data, including their quality and coverage limitations.
• Working knowledge of how model outputs are consumed by product interfaces and agentic systems, and sufficient software and product fluency to collaborate with Full-stack and AI Engineers.
• Active use of AI-assisted coding tools to accelerate modeling, hypothesis generation, and prototyping.
• Commitment to responsible analytical practices, including honest uncertainty quantification, documentation of model limitations, and sound judgment about whether to deploy a model.
• Track record of building and owning production-grade statistical models or analytical frameworks on which clients or products depend, with validation standards and deployment criteria.
• Direct experience presenting statistical methodology and model outputs to senior business stakeholders, including C-suite, and defending analytical choices in live client or commercial settings.
• Experience in agile, cross-functional product or case teams where analytical outputs must work with real-world data and short timelines.
• Bachelor’s degree in statistics, mathematics, economics, computer science, or a related quantitative field.

Nice To Haves

• Advanced degree in a quantitative field.
• Experience collaborating with engineers to translate model outputs into product features or automated workflows.

Responsibilities

• Own statistical modeling and analytical delivery for a product module workstream, from problem framing and data preparation through model building, validation, and production handoff.
• Design, build, and validate Bayesian statistical models, time-series forecasts, and domain-specific frameworks such as marketing mix, brand equity, price elasticity, and promotional lift models.
• Translate statistical outputs into structured, versioned data products for engineers, product interfaces, and agentic workflows, including interpretable uncertainty measures.
• Own model validation and evaluation, including back-testing, out-of-sample checks, sensitivity analysis, confidence bounds, and deployment-readiness standards.
• Design models and outputs for operation by the broader team and automated agentic workflows, with clear configuration and explicit uncertainty measures.
• Work with Data Engineers and the platform Data team to ensure model inputs are correctly structured, validated, and representative of real-world commercial data.
• Define model data requirements, including schemas, quality thresholds, expected ranges, and edge cases that may cause misleading outputs.
• Identify and diagnose upstream data-quality issues affecting model outputs and work with the data team to resolve root causes.
• Stay current with data sources and benchmarks relevant to the module, including media spend and attribution, brand tracking and panel, pricing, and promotional data.
• Present methodology, outputs, and recommendations to senior stakeholders in business terms that support decisions.
• Lead working sessions to stress-test assumptions, interpret outputs, and challenge methodology.
• Defend methodology, communicate uncertainty, and adjust the model narrative based on data and stakeholder input.
• Advance analytical methodology and share relevant developments and learnings with the broader data science team.

Benefits

• Annual discretionary performance bonus; the role may also be eligible for other discretionary compensation.
• 401(k) plan with a 4.5% company contribution, increasing after three years of service and fully vested upon start date.
• Bain pays 100% of individual employee premiums for medical, dental, and vision programs.
• Generous paid time off, including parental leave, sick leave, and paid holidays.
• Paid Life and Long-Term Disability insurance.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior