Senior Data Scientist, Marketing Analytics

As a Senior Data Scientist on the Product Marketing Analytics team, you will generate customer insights and build predictive models to support personalized, data-driven marketing communications. You will identify business problems, define analytical frameworks, and translate complex data into clear visualizations and actionable recommendations that inform marketing strategy, product adoption, and customer engagement. You will lead analytical initiatives end-to-end—from scoping and data preparation to modeling and delivery—while partnering with Engineering and Machine Learning teams to build scalable solutions. You will also leverage modern AI and LLM-based tooling to accelerate workflows and enhance analytical output. Minimum Qualifications Graduate degree in Business (quantitative focus), Statistics, Data Mining, Machine Learning, Analytics, Econometrics, Mathematics, Operations Research, Industrial Engineering, or a related field with 4+ years of experience OR Bachelor's with 6 years of relevant experience. Strong foundation in machine learning methods, including classification, regression, clustering, and ensemble techniques Proficiency in Python or Spark, with experience developing production-level analytical solutions Advanced SQL skills, including query optimization and data modeling in Snowflake Experience building and maintaining data visualization dashboards using Tableau or other visualization tools Preferred Qualifications Strong business acumen with the ability to connect analytical insights to strategic decision-making Experience with advanced marketing analytics techniques (e.g., time-series regression, marketing mix modeling, multi-touch attribution) Experience using LLMs and AI-assisted tooling to improve analytical productivity Experience presenting analytical findings and recommendations to senior leadership Experience managing end-to-end analytics projects with multiple competing priorities Experience partnering with technical and non-technical teams to translate business questions into analytical frameworks Experience working with incomplete or ambiguous data to deliver results in a dynamic environment