At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. This role is based in either New York, San Francisco, Mountain View, or Chicago. The Measurement Strategy & Testing team is seeking a Marketing Data Scientist to join its Incrementality Testing function. The team helps LinkedIn measure the incremental impact of marketing investments and evaluate measurement approaches. In this role, you will lead complex measurement initiatives from the initial business question through experiment design, execution, analysis, and final recommendation. You will partner closely with Product Marketing, Finance, Data Science, Media Activation, and business leaders to define the right hypotheses and KPIs, select rigorous and feasible measurement approaches, and translate findings into investment and optimization decisions. You will also help strengthen the team's measurement standards, tools, documentation, and automation so that high-quality testing can scale across business lines, marketing channels, and geographic markets. Responsibilities • Lead incrementality studies end to end, from defining the business question and assessing feasibility through test design, execution, analysis, and final recommendation • Serve as a testing and measurement subject matter expert, advising Product Marketing, Finance, Data Science, and activation partners on hypotheses, KPI selection, sample requirements, test design, and interpretation • Design and analyze experiments using methods such as randomized A/B tests, geo experiments, matched-market studies, synthetic controls, and Difference-in-differences • Geo-Based Measurement: Develop and analyze geo-experiments to measure marketing incrementality and validate MMM outputs • Communicate complex analytical concepts clearly and concisely to both technical and non-technical audiences, including senior business stakeholders • Prioritize, project-manage, and drive multiple analytics and testing workstreams forward under tight timelines, while proactively communicating progress, risks, tradeoffs, and decisions needed • Manage a portfolio of measurement projects independently, ensuring strong stakeholder alignment, clear documentation, and high-quality execution from intake through final recommendation • Develop and improve scalable processes, data standards, dashboards, automation tools, and analytical techniques that increase marketing effectiveness, measurement quality, and team efficiency • Stay current on the digital advertising and measurement ecosystem and creatively apply measurement solutions in ways that improve advertiser, member, and business outcomes Qualifications Basic Qualifications • Bachelor's degree in statistics, economics, applied mathematics, business analytics etc. • 5+ years of relevant industry or academic experience in data science, marketing science, experimentation, causal inference, econometrics, or a related analytical field • Working knowledge of causal inference methods, including geo-experimentation and observational approaches • Experience designing and analyzing experiments, such as A/B tests, geo experiments, or matched-market studies • Experience in SQL • Background in at least one programming language (e.g., R, Python, Scala) • Experience in applied statistics and statistical modeling in at least one statistical software package • Ability to communicate complex concepts clearly to stakeholders at varying technical levels Preferred Qualifications • MS or PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc. • Hands-on experience with geo-based experimentation, synthetic-control methods, difference-in-differences, Bayesian structural time-series models, or other approaches used to measure marketing incrementality • Experience with Marketing Mix Modeling, modeled attribution, conversion lift, brand lift, ROI analysis, or the validation and calibration of marketing measurement models • Experience with manipulating massive-scale structured and unstructured data • Familiarity with Bayesian modeling and its applications in marketing • Familiarity with AI-assisted coding and analytical tools used to accelerate prototyping, analysis, documentation, or workflow automation • Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field Suggested Skills • SQL • Python • Statistical Analysis • Data Storytelling • Data Interpretation LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $117,000 to $193,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.