Johnson & Johnson's Vision team is seeking to optimize marketing and campaign strategies to improve performance and sales by evaluating their effectiveness and identifying the best measurement frameworks.
Requirements
Proven experience with Regression Analysis, Marketing Mix Modeling (MMM), and other advanced statistical techniques.
Advanced knowledge of R and Python for data manipulation, analysis, and modeling.
Experience interpreting and communicating analytic results to analytical and non-analytical business partners
Hands-on experience with software frameworks or cloud platforms (e.g., AWS, GCP, or Azure).
A deep understanding of causal inference techniques like Propensity Scoring and Instrumental Variables.
Previous experience applying open-sourced MMM frameworks like Meta’s Robyn
Responsibilities
Lead the creation and maintenance of Marketing Mix Models (MMMs) to assess the contribution of various marketing channels to sales.
Design and execute Randomized Controlled Trials (RCTs) to evaluate the causal impact of marketing and campaign tactics.
Implement observational studies to inform decision-making when experimentation is not feasible.
Assess and deploy appropriate measurement methods (e.g., experimental vs. observational) based on the business question, data structure, and context.
Translate model outputs and analytical findings into actionable recommendations for the marketing and sales teams.
Build reproducible pipelines and robust scripts using R and Python to automate workflows.
Create compelling dashboards and visualizations for non-technical stakeholders to understand performance insights clearly.
Educational degree in quantitative field, such as Statistics, Mathematics, Computer Science, Data Science, Engineering, Economics, and/or related quantitative
Ability to travel both domestically and internationally may be required (~5-10%).
Ability to flex hours to accommodate multiple time zones when necessary.
Experience working in Commercial Analytics or directly supporting Marketing and Sales teams.
