Data Science Manager -Marketing

Empower; United States; Hybrid; USD 150,000 - 210,000; Full time

Job summary

Empower is seeking a Manager for Marketing Mix Modeling & Marketing Measurement to lead MMM initiatives and optimize marketing effectiveness across channels. You will own the end-to-end MMM process, partnering with Marketing, Finance, Data, and Technology to define outcomes, inputs, time periods, geographies, and model granularity, translating outputs into ROI/ROAS insights and budget scenarios.

You’ll manage external vendors, build scalable MMM playbooks, and advance internal capabilities for

Qualifications

• 8–12 years of experience in marketing analytics, science, econometrics, or related field.
• 5+ years hands-on MMM experience (development, validation, refresh, interpretation).
• Degree in statistics/data science or related quantitative field.
• Extensive MMM concepts knowledge: adstock, carryover, lagged effects, seasonality, trends.
• Experience interpreting MMM outputs: ROI, ROAS, marginal ROI, allocation scenarios.
• Ability to evaluate model specs, transformations, diagnostics, and calibration approaches.
• Experience with marketing data across digital and traditional channels.
• Proficiency in SQL and Python for data work and validation.
• Experience managing complex marketing measurement initiatives with external vendors.
• Strong knowledge of marketing/media concepts and data-driven decision-making.
• Strong communication skills for executive storytelling.

Responsibilities

• Own end-to-end MMM measurement process from business-question definition to adoption.
• Partner with Marketing, Media, Finance, Data, Technology and analytics teams to define outcomes, inputs, geographies, and model granularity.
• Review and challenge MMM model specifications, transformations, diagnostics, calibration approaches, and sensitivity analyses with external vendors.
• Translate MMM outputs into actionable insights: channel contribution, ROI, ROAS, and budget scenarios.
• Communicate model uncertainty, limitations, assumptions, and guardrails to stakeholders.
• Improve data quality and repeatability of marketing and external data used for measurement.
• Establish repeatable MMM refreshes, data quality checks, documentation, and version history.
• Manage external MMM vendors and drive knowledge transfer to internal teams.
• Develop reusable data definitions, model-review standards, and MMM playbooks.
• Plan transition of capabilities from external vendors to in-house teams.
• Integrate MMM with experimentation, incrementality, attribution, and brand measurement.

Skills

Marketing analytics

MMM

Cross-functional collaboration

Executive storytelling

Vendor management

Education

Bachelor’s or Master’s degree in Statistics/Data Science or related field

Tools

SQL

Python

Job description

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them.

Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself.

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.

We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age, race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.