Analyze user behavior across AI-powered product surfaces (conversational agents, content, search, recommendations) to understand the factors driving business outcomes
Track engagement and retention metrics such as session depth, feature adoption, and content consumption
Identify meaningful behavioral segments and turn observed trends into actionable recommendations
Synthesize signals from multiple data sources to form hypotheses about user behavior and business impact
Translate findings into clear, data-backed recommendations for product and marketing teams
Collaborate with cross-functional teams, including the customer insights analytics team, on behavioral analyses and strategies
Support experimentation initiatives by generating hypotheses and contributing to the experimentation roadmap
Write production-quality SQL and Python code for data extraction, transformation, and analysis
Work with data pipelines and transformation frameworks (e.g., dbt) to leverage and improve the data infrastructure
Identify gaps in data quality and instrumentation, and contribute to improvements
Document analyses and findings to ensure reproducibility and knowledge sharing
Requirements
More than 2 years of experience in data science, analytics, or a related field, with a focus on behavioral or product analytics
Experience working with behavioral event data (e.g., clickstream, session data, funnel metrics)
Excellent SQL skills and the ability to query complex datasets from multiple sources
Proficiency in Python for data analysis and manipulation
Ability to work independently with messy or incomplete datasets
Strong problem-solving skills with a proactive, consultative approach
Demonstrated ability to communicate findings clearly to non-technical stakeholders