Data Science Manager -Marketing at Empower in KA Bangalore

Job description

• Manager, Marketing Mix Modeling & Marketing Measurement

Responsibilities

• Serve as a senior individual contributor responsible for advancing Empower’s marketing effectiveness and marketing measurement capabilities, with Marketing Mix Modeling (MMM) as the primary focus.
• Own the end-to-end Marketing Mix Modeling measurement process, from business-question definition and data readiness through model review, validation, refreshes, interpretation, and stakeholder adoption.
• Partner with Marketing, Media, Finance, Data, Technology, Analytics, and other cross-functional teams to define business outcomes, media inputs, control variables, time periods, geographies, and appropriate model granularity.
• Partner with external MMM vendors and technical modeling teams to review and challenge model specifications, assumptions, transformations, diagnostics, calibration approaches, sensitivity analyses, and results.
• Translate MMM outputs into actionable marketing investment insights, including channel contribution, incremental impact, return on investment (ROI), return on ad spend (ROAS), marginal ROI, response curves, diminishing returns, and budget-allocation scenarios.
• Communicate model uncertainty, limitations, assumptions, and decision guardrails to business and executive stakeholders.
• Partner with data owners to improve the quality, consistency, and repeatability of marketing, media, business, and external data used for marketing measurement.
• Establish repeatable processes for MMM refreshes, data and model quality checks, documentation, validation, and version history.
• Manage external MMM and marketing measurement partners, evaluate deliverable quality, resolve issues, and facilitate knowledge transfer to internal teams.
• Develop reusable data definitions, model-review standards, documentation, and marketing measurement playbooks.
• Assess which MMM activities should remain vendor-supported and which data, validation, analytical, and modeling capabilities can progressively transition in-house.
• Integrate MMM insights with complementary marketing measurement approaches, including experimentation, incrementality testing, campaign measurement, attribution, and brand measurement.
• Support brand communication measurement by interpreting brand-health, brand-lift, and advertising-effectiveness studies and connecting findings to media strategy and business outcomes.
• Build repeatable internal MMM standards, knowledge, and processes and contribute to the long-term marketing measurement roadmap.

Requirements

• 8–12 years of relevant experience in marketing analytics, marketing science, econometrics, advanced analytics, or a related field.
• 5+ years of hands-on experience with Marketing Mix Modeling (MMM), including model development, validation, model refreshes, interpretation, or operationalization.
• Bachelor’s or Master’s degree in Statistics, Data Science, or a related quantitative field.
• Extensive knowledge of Marketing Mix Modeling concepts and methodologies, including adstock/carryover, lagged effects, saturation, diminishing returns, seasonality, trends, control variables, multicollinearity, model calibration, and uncertainty.
• Experience interpreting MMM outputs, including channel contribution, incremental impact, response curves, ROI, ROAS, marginal ROI, and marketing budget-allocation scenarios.
• Demonstrated ability to evaluate model specifications, assumptions, transformations, diagnostics, sensitivity analyses, calibration approaches, and business reasonableness.
• Experience working with marketing and media data across digital and traditional channels, including media spend, exposure, response, business outcomes, and relevant external factors.
• Working proficiency in SQL and Python for data investigation, data quality checks, analysis, and model-output validation.
• Experience independently managing complex marketing measurement initiatives involving external vendors and cross-functional stakeholders without formal people-management responsibility.
• Strong knowledge of marketing and media concepts across digital and traditional channels.
• Strong analytical judgment and the ability to translate statistical and model results into commercially relevant marketing and investment decisions.
• Strong stakeholder management, vendor management, prioritization, and execution skills.
• Strong written and verbal communication skills, including executive-ready storytelling and the ability to communicate complex marketing measurement concepts clearly.
• Experience building a Marketing Mix Modeling, marketing science, or marketing measurement capability from the ground up, including transitioning selected capabilities from external vendors to internal teams.
• Experience using experimentation and incrementality methodologies, including geo experiments, geo tests, matched-market studies, lift studies, or similar approaches to validate or calibrate marketing measurement.
• Experience with brand communication measurement, brand-health tracking, brand-lift studies, or advertising-effectiveness research.
• Experience in financial services, retirement, or wealth management.

Skills

Required

• Marketing Mix Modeling (MMM)
• SQL
• Python
• Data analysis
• Model validation
• Stakeholder management
• Vendor management
• Communication
• Analytical judgment

Preferred

• Brand communication measurement
• Financial services knowledge