What You Will Do
Advanced Analytics & Problem Solving
-Turn vague business questions into structured, measurable analytical problems using hypothesis-driven analysis, root cause analysis, and systems thinking.
-Conduct exploratory data analysis (EDA), time series analysis, segmentation/clustering, and cohort analysis to uncover business opportunities and solve complex catalog challenges.
-Design and execute experiments, applying statistical inference, hypothesis testing, and sampling methodologies to validate business impacts.
-Utilize Python/R and advanced analytics techniques (including feature engineering) to extract actionable insights from large-scale data.
Data Engineering & Infrastructure Support
-Design, build, and maintain scalable ETL/ELT pipelines, data lake architecture, and API integration using Python and modern data warehouses (Snowflake/BigQuery).
-Implement data quality checks, maintain core data tables/lineage, and optimize SQL queries to ensure backend reliability, performance, and self-serve analytics enablement.
Business Partnership & Solution Design
-Collaborate closely with catalog and cross-functional business teams to translate requirements into data models, analytical frameworks, and dashboards.
-Partner with external teams on special projects to investigate, diagnose, and mitigate business challenges through data.
Continuous Improvement
-Stay current with evolving data technologies, tools, and industry best practices.
-Proactively identify opportunities to enhance data infrastructure and analytical capabilities.