Sr Analyst, Marketing Science

Sr Analyst, Marketing Science (Finance)

The Senior Analyst of Marketing Science will sit at the intersection of marketing analytics, data science, and experimentation, helping shape how we measure, optimize, and forecast the impact of marketing across channels. The ideal candidate will leverage advanced analytical techniques to directly inform budget allocation, audience strategy, and channel optimization.

This role requires a strong foundation in cohort segmentation, lifetime value modeling, propensity modeling, and experimentation frameworks, with hands‑on experience in Geolift testing and Marketing Mix Modeling (MMM).

• Cohort & customer analytics
  • Develop and maintain cohort frameworks to understand acquisition, engagement, retention, and churn across key marketing channels.
  • Build, validate, and operationalize LTV models that inform budget allocation, media efficiency, and payback windows.
  • Build propensity-to-engage/convert models and surface audiences that can be activated across paid media, CRM, and onsite experiences.
  • Identify and continuously refine high‑value actions (HVAs) that best predict downstream LTV, retention, and revenue, and translate them into marketing optimization levers.
• Experimentation & causal measurement
  • Design, implement, and analyze A/B tests across channels (paid media, CRM, onsite), including power analysis calculations, sample‑size determination, and statistical significance assessments.
  • Lead incrementality testing, including test/control frameworks and causal inference approaches to quantify true marketing lift.
  • Design and execute Geo Lift/geo‑experiments to measure regional marketing impact when user‑level randomization is not feasible.
  • Partner with Data Science to ensure methodological rigor, documentation, and reproducibility of all experiments.
• Modeling & advanced analytics
  • Build MMM models to estimate the incremental impact of media channels and inform optimal budget allocation by channel, geography, and time period.
  • Retention Drivers Model (Random Forest + SHAP):
    Identify key behaviors, demographics, or campaign touchpoints predicting long‑term retention.
• Measurement, reporting & data products
  • Build and maintain automated dashboards and reports (Looker, Tableau, etc.) to measure end‑to‑end campaign effectiveness across paid media, CRM, search, and onsite channels.
  • Own recurring performance readouts (weekly/monthly/quarterly), synthesizing drivers of performance, cohort trends, and test results into clear narratives for executives and cross‑functional partners.
  • Work with data engineering, Mar Tech, and analytics partners to ensure robust instrumentation, accurate data pipelines, and consistent marketing taxonomies.
• Stakeholder partnership
  • Collaborate with Growth Marketing, Brand, CRM, and Product teams to define measurement plans, success metrics, and learning agendas for major campaigns and product initiatives.
  • Communicate complex analytical findings in a clear, concise way tailored to non‑technical audiences, using storytelling and data visualization to drive alignment and decisions.
  • Advocate for data‑driven decision‑making and experimentation culture across the marketing organization.

• 4–6 years of professional experience in marketing analytics, data science, or a related field.
• Proficiency in advanced data management languages such as SQL and tools such as Google Big Query.
• Familiarity with programming languages like R, Python, or Java.
• Strong written communication skills, including crafting and presenting data‑driven analyses and insights to articulate performance and opportunities to key stakeholders.
• Strong verbal communication skills and adept at pitching persuasive presentations.
• Strategic thinking skills, being able to articulate how social and digital recommendations will impact Yahoo businesses at large.
• Proficient in data visualization tools (e.g., Tableau, Looker).
• Proven experience with cohort segmentation and creating LTV models.
• Strong knowledge of propensity to engage models and identifying high‑value actions.
• Hands‑on experience with experimentation frameworks, including A/B testing and incrementality testing.
• Experience…