Employer description & source details
develop and maintain models that guide paid media investment, including spend-response curves, player lifetime value forecasts, user acquisition forecasts, and budget optimization approaches measure the effectiveness and incremental impact of advertising using sound statistical methods work on Ads initiatives to improve player experience while optimizing monetization, enhance our strategy in ads bidding, etc. translate model outputs into clear recommendations on where and when to invest, explaining expected outcomes, uncertainty, and key assumptions to marketing and finance partners. partner with User Acquisition, Ads, Finance, and Analytics Engineering teams to turn reliable data science into tools and workflows that support recurring marketing decisions 3+ years of experience as a Data Scientist. Background in performance marketing and mobile free-to-play gaming is strongly preferred excellent analytical and problem-solving skills, with a track record of using data to drive meaningful outcomes preferred experience in applying marketing modeling techniques e.g., media mix modeling, time series forecasting, segmentation/clustering advanced SQL and hands-on Python skills for working with large datasets, developing analyses, and building reliable, scalable models; exposure to Google Cloud Platform and BigQuery is a plus working knowledge of visualization tools: Looker (Preferred), QlikView, Tableau, or PowerBI proficiency in developing and operating production data science workflows, including orchestration with tools such as Airflow and containerization with Docker; cloud deployment, CI/CD, and monitoring experience is a plus strong communication skills and the ability to explain clearly to both technical and non-technical stakeholders, influencing decision-making throug
Extracted skills: python, go, sql, docker, tableau, recruiting, finance, operations