Marketing Data Scientist, Measurement & Experimentation

About the Role

LinkedIn, the leading professional networking platform, is dedicated to fostering economic opportunities worldwide. Our services enable users to connect, discover career opportunities, enhance skills, and gain insights daily. We also invest heavily in our employees' growth, nurturing a culture rooted in trust, inclusivity, care, and enjoyment where everyone can thrive.

Join us in revolutionizing how the world works. This position supports a hybrid work model, balancing remote and on-site presence based on business needs, and is located primarily in New York, San Francisco, Mountain View, or Chicago.

Job Overview

The Measurement Strategy & Testing team seeks a Marketing Data Scientist focused on Incrementality Testing. This role involves leading in-depth measurement projects from conceiving business questions to designing experiments, conducting analyses, and delivering actionable recommendations. The ideal candidate will collaborate across teams including Product Marketing, Finance, Data Science, Media Activation, and business leadership to define hypotheses, key performance indicators, choose appropriate measurement techniques, and convert results into strategic investment decisions.

This position also entails improving the team's measurement capabilities by enhancing standards, tools, documentation, and automating processes to enable scalable and high-quality testing across various business segments and geographies.

Key Responsibilities

• Own end-to-end incrementality testing: defining business objectives, evaluating feasibility, designing experiments, executing tests, analyzing data, and communicating final insights and recommendations.
• Provide expert advice on experimental design, hypothesis formulation, KPI selection, sampling requirements, and outcome interpretation to partners in marketing, finance, and data science.
• Implement and assess experiments such as randomized A/B tests, geographic experiments, matched-market comparisons, synthetic controls, and difference-in-differences analysis.
• Develop and evaluate geo-experiments specifically targeting marketing effectiveness and validating marketing mix modeling (MMM) results.
• Convey complex analytical findings clearly to both technical teams and business executives.
• Manage multiple analytics projects simultaneously with effective prioritization, clear communication about progress and risks, and transparent decision-making processes.
• Independently supervise a diverse portfolio of measurement studies, ensuring stakeholder alignment, thorough documentation, and high-quality execution throughout the project lifecycle.
• Enhance scalable processes, standardized data metrics, dashboards, automation, and analytical methods to boost marketing impact and operational efficiency.
• Keep abreast of the evolving digital advertising landscape and leverage innovative measurement techniques to drive improved outcomes for advertisers, members, and the business.

Required Qualifications

• Bachelor's degree in relevant quantitative fields such as statistics, economics, applied mathematics, or business analytics.
• Minimum of five years’ experience in data science, marketing analytics, experimentation, causal inference, econometrics, or related analytical domains.
• Proficient in causal inference methods including geo-experimentation and observational study approaches.
• Experience designing and interpreting experiments like A/B tests, geo experiments, and matched-market designs.
• Skilled in SQL and familiar with at least one programming language such as R, Python, or Scala.
• Experience utilizing statistical software for modeling and applied statistical analysis.
• Effective communication skills for explaining intricate concepts to stakeholders with diverse technical backgrounds.

Preferred Qualifications

• Advanced degree (Master’s or PhD) in quantitative disciplines like statistics, operations research, computer science, econometrics, engineering, or applied mathematics.
• Hands-on experience with geo-experimental design, synthetic control techniques, difference-in-differences, Bayesian structural time-series, or comparable methods for marketing incrementality assessment.
• Familiarity with Marketing Mix Modeling, attribution modeling, lift analysis, ROI evaluation, and validating marketing measurement strategies.
• Ability to manipulate and analyze large-scale structured and unstructured datasets.
• Understanding of Bayesian modeling techniques and their marketing applications.
• Experience with AI-assisted coding or analytical tools to accelerate prototype development, analysis workflows, and documentation.
• A strong passion for marketing and consumer analytics, with eagerness to stay updated on current developments.

Compensation Details

The salary range for this position is $117,000 to $193,000 annually, with actual pay determined based on individual skills, experience, certifications, and location. Additional compensation may include annual bonuses, stock options, benefits, and other incentives.

Additional Information

LinkedIn embraces diversity and is an equal opportunity employer committed to fostering an inclusive environment. Applicants are considered without discrimination based on legally protected characteristics.

The company provides reasonable accommodations for individuals with disabilities throughout the hiring process. Examples of accommodations include accessible interview locations, alternate document formats, sign language interpreters, and service animals. Requests are typically addressed within three business days.

LinkedIn adheres to fair pay transparency policies and complies with related equal opportunity laws, including the San Francisco Fair Chance Ordinance regarding consideration of applicants with arrest or conviction records.

Applicants can expect transparent data privacy practices regarding personal information handling.