Senior Data Scientist, Product Analytics

Adobe Adobe · Enterprise · San Jose, CA +2

Senior Data Scientist at Adobe focused on product analytics, data architecture, and applying predictive modeling/ML to enhance customer experiences. The role involves partnering with product and engineering teams, analyzing usage patterns, automating data pipelines, building dashboards, driving experimentation, and implementing recommendation models. Requires strong SQL, experimentation, and statistical skills.

What you'd actually do

  1. Partner with product and engineering teams to understand existing product instrumentation and help bridge gaps in data streams to assist data science initiatives.
  2. Analyze product usage patterns to better understand customer behavior including acquisition, engagement, conversion, and retention.
  3. Automate and optimize data pipelines using SQL and/or Python-based ETL Frameworks.
  4. Build and maintain various dashboards to inform the team about the state of the business, as well as to alert business partners when issues occur.
  5. Architect and implement models to recommend personalized in-app content.

Skills

Required

  • MS or Ph.D. in data science, computer science, statistics, applied mathematics, engineering, or economics, or equivalent experience.
  • 5 - 7+ years of relevant data science experience.
  • Experience translating business questions into data analytics approaches.
  • Strong proficiency in querying and manipulating large datasets using SQL-like languages (Hive, Spark, etc.).
  • Experience developing and operationalizing consistent approaches to experimentation, using appropriate statistical techniques to reduce bias and interpret statistical significance.
  • Proficiency with descriptive and inferential statistics (i.e., t-test, chi-square, ANOVA, correlation, regression, etc.) to understand customer engagement and generate hypotheses.
  • Experience crafting data visualizations and storytelling to efficiently communicate analysis results to 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.
  • Possess natural curiosity and technical competence, being capable of asking critical questions and always ready to address any challenges.
  • Experience addressing an executive level audience.
  • Excellent communication, relationship skills, and a strong teammate.

Nice to have

  • Experience in product instrumentation is a plus.

What the JD emphasized

  • strong data architecture
  • predictive modeling and machine learning
  • product instrumentation
  • experimentation
  • statistical techniques