Senior Analyst Data science- Marketing

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Role Overview

Empower India Data Science is seeking a Senior Analyst, Data Science - Paid Media Measurement & Media Mix Modeling (Marketing Analytics). This hands-on individual-contributor role is approximately 60% focused on paid media measurement and experimentation and 40% on Media Mix Modeling (MMM). The Senior Analyst will help ensure paid campaigns are configured for reliable measurement, trace how media activity is captured from platform setup through first-party outcomes, design and evaluate experiments, and use those learnings alongside MMM to assess marketing effectiveness and guide investment decisions.

This is an opportunity to help build a modern paid media measurement and MMM capability from the ground up for a large U.S. organization, with hands-on exposure to shaping tracking standards, experimentation, data workflows, and how measurement is operationalized at scale.

Key Responsibilities

• Set up, traffic, or independently quality-assure paid media campaigns across paid search, paid social, programmatic display/video, CTV, and related channels; review campaign structure, audiences, placements, creatives, budgets, bidding, optimization events, naming conventions, and taxonomies that affect measurement.
• Translate campaign objectives into measurement plans and implement or validate conversion tracking, including KPIs, conversion definitions, attribution windows, UTMs/click IDs, pixels/tags, ad-server tracking, platform conversion APIs, enhanced/offline conversions, and first-party event integrations.
• Trace measurement end to end from impression or click through digital conversion and downstream first-party outcomes; diagnose broken or duplicate events, incorrect mappings, attribution differences, and discrepancies across media platforms, ad servers, web analytics, and internal reporting.
• Design and evaluate paid-media experiments such as A/B or platform tests, creative/audience/bidding tests, lift studies, geo or matched-market tests, and holdout-based incrementality studies; define hypotheses, treatment/control design, sample and power considerations, measurement windows, guardrails, and validity risks.
• Analyze paid-media performance and experiment results using measures such as reach, frequency, CPM, CPC, CTR, conversion rate, CPA, ROAS, lift, incremental conversions, and cost per incremental outcome; distinguish attributed performance from incremental impact and recommend practical actions.
• Support recurring MMM by preparing, reconciling, and validating media, business, and external inputs; assist with model refreshes, diagnostics, data-quality checks, assumptions, and documentation across digital and traditional channels.
• Interpret MMM outputs including channel contribution, incremental impact, ROI/ROAS, marginal returns, response curves, and budget scenarios; connect MMM findings with experiment and campaign evidence, while clearly communicating uncertainty, limitations, and decision guardrails.
• Build repeatable dashboards, test readouts, QA standards, and measurement documentation, and partner with Media, Performance Marketing, MarTech, Web Analytics, Data Engineering, Finance, agencies, platforms, and measurement partners to improve measurement quality and adoption.

Qualifications & Experience

• Bachelor's or Master's degree in Statistics, Economics, Marketing Analytics, Data Science, Business Analytics, Computer Science, Engineering, or a related quantitative discipline.
• 5-8 years of experience in paid media, performance marketing, digital advertising operations, marketing analytics, marketing measurement, data science, or a closely related field.
• At least 4 years of direct hands-on experience setting up, trafficking, optimizing, or quality-assuring campaigns in major advertising platforms such as Google Ads, Meta Ads Manager, LinkedIn Campaign Manager, Microsoft Advertising, Campaign Manager 360, Display & Video 360, Search Ads 360, or comparable platforms.
• Hands-on experience configuring and validating digital conversion measurement across tags/pixels, conversion events, tag managers, ad-server tracking, platform APIs, enhanced or offline conversions, web analytics, and first-party data integrations.
• Experience designing and analyzing paid-media experiments, including A/B tests, platform experiments, lift studies, geo or matched-market tests, and holdout/incrementality tests.
• At least 2 years of hands-on experience supporting MMM or closely related econometric marketing measurement, including data preparation, model refresh or validation, output interpretation, and business application.
• Experience independently delivering complex measurement or analytics work and collaborating across Media, Marketing, MarTech, Analytics, Data Engineering, Finance, agencies, or external measurement partners; financial-services or other regulated-industry experience is a plus.

Skills & Capabilities

• Strong command of paid-media measurement architecture, including campaign mechanics, conversion tracking, attribution windows, de-duplication, modeled conversions, server/API event feeds, first-party integrations, and cross-platform troubleshooting.
• Strong grounding in experimental design and causal measurement, including treatment/control design, randomization and holdouts, power and sample-size considerations, statistical significance, confidence intervals, lift, incrementality, and practical significance.
• Strong SQL and Python skills for extracting, joining, validating, analyzing, and automating marketing data; experience with web analytics, tag-management, and BI/visualization tools such as Adobe Analytics, Google Analytics, Google Tag Manager, Adobe Tags, Tableau, Power BI, QuickSight, Looker, or comparable tools.
• Working knowledge of MMM concepts and diagnostics, including adstock/carryover, saturation, seasonality, controls, multicollinearity, calibration, uncertainty, channel contribution, ROI/ROAS, marginal returns, response curves, and budget scenarios; ability to triangulate MMM findings with experimental evidence.
• Strong analytical problem solving, data-quality discipline, business judgment, communication, and stakeholder-management skills, with the ability to identify measurement issues, explain uncertainty, and translate findings into clear actions.

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.