Data Science Manager -Marketing

Empower LLC; Bengaluru; On-site; INR 4,500,000 - 7,000,000; Full time

Job summary

Empower LLC in Bengaluru seeks a senior analytics leader to own Marketing Mix Modeling (MMM) and marketing measurement, partnering across Marketing, Finance, Data, and Tech. You will translate complex MMM outputs into actionable insights for investment decisions.

The role requires deep MMM expertise, strong stakeholder communication, and experience managing external vendors to drive internal capability growth.

Qualifications

• 8–12 years in marketing analytics, marketing science, econometrics, or related field.
• 5+ years with Marketing Mix Modeling (MMM): development, validation, or operationalization.
• Bachelor’s or Master’s in Statistics, Data Science, or related quantitative field.

Responsibilities

• Own end-to-end MMM measurement process from question to adoption.
• Collaborate with Marketing, Finance, Data, Tech, Analytics and more.
• Review, calibrate, and refresh MMM with vendors and internal teams.
• Translate MMM outputs into ROI, ROAS, and budget allocation insights.
• Communicate uncertainty, assumptions, and guardrails to executives.
• Establish repeatable MMM processes, data quality checks and version history.

Skills

MMM

Marketing Analytics

SQL

Python

Stakeholder Mgmt

Vendor Mgmt

Cross-functional Collaboration

Education

Statistics/Data Science degree

Tools

SQL

Python

Job description

# **Manager, Marketing Mix Modeling & Marketing Measurement**## What You Will Do* 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.## **What You Will Bring*** 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.## What Will Set You Apart* 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.