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We're looking for a highly analytical and technically proficient Product Analyst to join our team. You will play a crucial role in driving the success of our Logistics product improvements and advancing our logistics-wide experimentation efforts. The ideal candidate has a strong background in data analysis, a passion to improve data driven product improvements and a proven ability to translate complex data into actionable product insights. This role requires hands-on expertise with various data tools and a solid understanding of data pipelines.
Job Responsibility:
Product Performance Analysis: Support analytics
Define, monitor, and report on key product metrics to assess product health and impact of releases
Experimentation: Design, set up, and analyze product experiments across various features and product surfaces
Develop hypotheses, determine appropriate statistical methodologies, and clearly communicate the results and recommendations to product managers and stakeholders
Data Manipulation & Reporting: Write, optimize, and execute complex SQL queries to extract and manipulate data from large, disparate databases
Utilize Python (e.g., pandas, NumPy, statistical libraries) for advanced data cleaning, statistical modeling, and analysis as needed
Develop and maintain dynamic dashboards and reports using data visualization tools like Looker and Tableau to monitor business and product performance in real-time
Data Infrastructure & ETL: Demonstrate hands-on experience and comfort with understanding, troubleshooting, and occasionally contributing to ETL pipelines to ensure data quality, consistency, and availability for analysis
Collaborate with Backend and Data Engineering teams to define necessary tracking and logging for new features
Strategic Insight: Partner closely with Product Managers, Engineers, Data Scientist and UX/UI Designers to influence the product roadmap based on quantitative data and analytical insights
Present findings, insights, and recommendations clearly
Requirements:
Strong experience as a Product Analyst or data analytics
Expert-level proficiency in SQL for querying, aggregating, and analyzing large datasets
Hands-on experience with Python for data analysis, including statistical packages
Proven background in experimentation including hypothesis formulation, sample size calculation, statistical significance, and interpretation of results
Familiarity with cloud data platforms (e.g., AWS, GCP, Azure) and distributed processing frameworks
Proficiency in creating and managing dashboards, reports, and data models using Looker and/or Tableau
Familiarity and comfort with ETL processes and data warehousing concepts
Excellent communication skills with the ability to clearly articulate complex analysis and trade-offs