Uncovering how customers engage with and gain value from Adobe's products to inform marketing strategies.
Requirements
- Strong proficiency in querying and manipulating large datasets using SQL-like languages (Hive, Spark, etc.) within a cloud data platform (Databricks or similar)
- Proficiency in Python for data analysis and modeling
- Experience translating business questions into data analytics approaches
- Proficiency with descriptive and inferential statistics (i.e., t-test, chi-square, ANOVA, correlation, regression, etc.) to understand customer engagement and generate hypotheses
- Hands‑on with visualization tools like Tableau, Looker, Power BI, or equivalent libraries for dashboards and storytelling for both technical and non-technical audiences
- Knowledge of relevant tools in this field such as Hadoop, Hive, Splunk, Spark, Tableau, Excel (Charting and Pivot-Tables), and Power BI
Responsibilities
- Analyze product usage patterns and customer journeys to uncover behavioral insights related to acquisition and retention—translating findings into actionable marketing strategies
- Drive experimentation, including the design, execution, and evaluation of A/B and multivariate tests across marketing and product to optimize strategy
- Build predictive models and machine learning solutions to personalize content, segment users, and forecast behaviors such as churn, LTV, or feature adoption, and inform measurement strategies
- Proactively identify user trends and market signals, turning them into high-impact recommendations that craft decisions and planning
- Partner cross-functionally to craft compelling data stories and visualizations to present insights clearly to technical and non-technical audiences, including marketers, designers, product managers, and executives
- Understand and improve product instrumentation by collaborating with insights and data engineering teams to ensure data completeness, quality, and usefulness for analysis
- Guide automation and optimization of data pipelines using SQL and Python-based ETL frameworks; ensure scalable, reliable, and reproducible workflows for both exploratory and production use
Other
- Seeking a highly curious, customer-obsessed Senior Data Scientist
- 7+ years of data science experience, especially in marketing analytics, product analytics
- Natural curiosity, creative thinking, strong business sense, and polished communication skills
- Strong teammate who thrives in a diverse, inclusive culture that values fresh ideas from everyone
- MS or PhD in Data Science, Statistics, Computer Science, Mathematics.
