Build and maintain causal inference frameworks, i.e. Mix Media Modeling, muti-touch attribution and regression analysis, to measure marketing effectiveness across channels and initiatives Automate the calculation of ROI and optimization opportunities Build automated pipelines to productionize the output of causal inference and ROI frameworks Communicate clearly across disciplines: Provide clear, consistent, and concise communication with varied stakeholders Create decision-ready narratives that connect activity to Minecraft's business outcomes Automate uplift calculations from marketing A/B tests treatment and control groups and clearly highlight opportunities for future experiments Collaborate with stakeholders to understand how to best measure success Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. 5 years of experience with causal inference frameworks for marketing attribution analysis such as MMM, multi-touch attribution, A/B tests and regression analysis.