Senior Manager, Data Science

Job Title: Senior Manager, Data Science Company: Bain & Company Job Category: Data Science Roles & Responsibilities: You will be part of a team building Bain’s integrated suite of agentic decisioning tools that gives large organizations always\-on intelligence across their most important growth decisions. The role sits at an intersection few organizations can offer: the analytical depth and client access of a top\-tier consultancy, the technical ambition of a product company, and engineering work at the frontier of applied AI. This is a startup inside an established company. You get genuine early\-stage ownership and 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. The Data Scientist owns the statistical and analytical core of a Growth AI Performance System product module, designing, building, and validating the models that power client\-facing outputs across marketing ROI, brand strategy, or pricing and commercial analytics. You will work within a blended product and case team, sitting under the Tech Lead and working alongside the Full\-stack Engineer to translate model outputs into scalable, repeatable product features that consulting teams and their clients depend on in live engagements. This role sits at the intersection of applied statistics, product thinking, and delivery. The problems you will work on (marketing mix modeling, brand equity measurement, price elasticity, promotional lift) are hard analytical problems with decades of methodology behind them and an enormous amount of client\-specific noise in front of them. The job is to produce outputs that are credible in both directions: to a methodologically literate peer and to a CMO or Category Director who needs to make a decision. * Own the statistical modeling and analytical delivery for your product module workstream (from problem framing, hypothesis development, and data preparation through model build, validation, and production handoff), working under the direction of the Tech Lead and in close partnership with the Full\-stack Engineer * Design, build, and validate Bayesian statistical models, time\-series forecasts, and domain\-specific analytical frameworks (marketing mix models, brand equity models, price elasticity and promotional lift models) that are methodologically sound, production\-ready, and defensible to senior audiences * Translate statistical model outputs into structured, versioned data products that the Full\-stack Engineer and AI Engineering team can consume for product interfaces and agentic workflows; design outputs with interpretable confidence and uncertainty measures that professional users can act on * Own the validation and evaluation framework for your workstream: back\-testing, out\-of\-sample checks, sensitivity analysis, and documented confidence bounds; define and enforce deployment\-readiness standards consistently before model outputs reach live client environments * Design models and outputs so they can be operated by the broader team and, over time, by automated agentic workflows: clear configuration, interpretable outputs, and explicit uncertainty measures that do not require the original modeler to interpret * Present model methodology, outputs, and recommendations directly to senior stakeholders, translating complex statistical concepts into business terms that drive decisions * Lead and facilitate working sessions with teams where model assumptions are stress\-tested, outputs are interpreted, and methodology is challenged * Operate as a credible, composed analytical voice in stakeholder settings: able to defend methodology under challenge, acknowledge uncertainty honestly, and adjust the model narrative when the data or the room requires it * Drive innovation in analytical methodology: stay current with advances in Bayesian inference, marketing mix modeling, brand measurement, and commercial analytics; bring relevant methodological improvements into the product and share learnings with the broader data science team Work Location: London, ENG, UK Availability: Full time

We are looking for data scientists who see how to make a product module smarter and bring that instinct to every sprint without being asked, and who are comfortable with problems that do not have a known answer. The work involves Bayesian statistical modeling, experiment design, and data problems with no off\-the\-shelf answer. Experience with agentic systems matters: understanding how model outputs feed into agentic workflows and evaluation harnesses, and entity resolution across messy enterprise data. This is applied AI in production, at scale, with real users depending on what you build. The field is moving quickly and the team is built to move with it, so the willingness to keep learning counts for as much as what you already know. * Deep Bayesian statistical expertise: able to design prior structures, diagnose convergence issues, stress\-test assumptions, and defend inferences to both methodologically literate peers and non\-technical senior audiences * Strong domain knowledge in at least one product module area: marketing mix modeling and media ROI measurement, brand equity and consumer choice modeling, or pricing and revenue growth management analytics: with the methodological depth to produce outputs that clients trust * Strong Python proficiency for statistical modeling and data analysis: probabilistic programming, scientific computing, and the software engineering discipline to produce model code that can be handed off to engineers cleanly * Experience designing and running experiments (A/B testing, out\-of\-sample validation, back\-testing, and sensitivity analysis), and interpreting results with appropriate statistical rigor * Ability to translate statistical model outputs into structured data products that engineers can consume and agentic workflows can operate: clear schemas, documented uncertainty measures, and explicit confidence bounds * Familiarity with the data sources and benchmarks relevant to commercial analytics: media platform data, panel data, point\-of\-sale data, pricing and promotional data, and the quality and coverage limitations that affect modeling choices * Working knowledge of how model outputs are consumed by product interfaces and agentic systems; enough software and product fluency to collaborate effectively with Full\-stack Engineers and AI Engineers on how models are integrated * Native AI fluency: active use of AI\-assisted coding tools to accelerate modeling work, generate and test hypotheses faster, and prototype analytical approaches before committing to full model builds * Demonstrated commitment to responsible analytical practices: honest uncertainty quantification, clear documentation of model limitations, and the judgment to know when a model should not be deployed to a live client engagement Experience Education Bachelor’s degree in statistics, mathematics, economics, computer science, or a related quantitative field; advanced degree is an advantage but not required U.S. Compensation Information Compensation for this role includes base salary, annual discretionary performance bonus, 401(k) plan with an annual employer contribution based on years of service and Bain’s best in class benefits package (details listed below). Some local governments in the United States require a good\-faith, reasonable salary range to be included in job postings for open roles. The estimated annualized compensation for this role is as follows: * In Massachusetts, the good\-faith, reasonable annualized full\-time salary range for this role is between $172,000 \- $206,500; placement within this range will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level * In Illinois, the good\-faith, reasonable annualized full\-time salary range for this role is between $164,500 \- $197,500; placement within this range will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level * Annual discretionary performance bonus * This role may also be eligible for other elements of discretionary compensation * 4\.5% 401(k) company contribution, which increases after 3 years of service and is 100% vested upon start date Bain \& Company’s comprehensive benefits and wellness program is designed to help employees achieve personal independence, protection and stability in the areas most important to you and your family. For all other locations, the good\-faith, reasonable annualized full\-time salary range for this role is commensurate with competitive geographic market rates for this role and will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level. Key Skills: Data Science Salary: GBP 172000 - 206500 per yearly