Data Science – Product Analytics

Job Description

Product Data Scientist, Employee Experience & Productivity, IS&T | Apple

The Tone:
This is a full-time role at Apple. Apple’s Information Systems and Technology (IS&T) organization is the engine powering the company. This position within the Employee Productivity & Support Data Science team is crucial for enriching internal product data with business context. You will produce insights that enable intelligent decisions, ultimately improving how Apple’s internal productivity tools and platforms evolve.

The TL;DR
• Role: Mid-Level
• Team: Employee Productivity & Support Data Science team, within IS&T’s Product group.
• Mission: To enrich internal product data with business context and provide insights that improve employee experience and productivity.
• Tech Stack: SQL, Tableau, Python, R, AI tools, GitHub, Looker.

What You’ll Actually Do
• Partner with product leaders: Partner with product leaders and program managers to understand their needs, translate business questions into data problems, and deliver recommendations grounded in evidence.
• Prepare data: Extract, clean, transform, and validate data from multiple product and platform systems, creating reliable datasets for analysis and visualization.
• Visualize insights: Build and maintain dashboards and reports in Tableau, actively consuming these assets to identify trends, surface anomalies, and communicate insights back to stakeholders.
• Conduct deep-dives: Conduct deep-dive analyses on product usage and adoption data to answer questions that existing dashboards do not address, packaging findings into clear, audience-ready deliverables.
• Accelerate with AI: Utilize AI tools to accelerate insight generation, including summarizing patterns, classifying data, and enhancing the speed and depth of analytical work, while validating outputs to ensure accuracy.

The Must-Haves
• Background: Bachelor’s degree with 3+ years of relevant experience, or a Master’s degree with 2+ years of relevant experience, in data analytics, business intelligence, data science, or a related quantitative field.
• Experience: 3+ years of hands-on experience writing SQL to extract, transform, and analyze data from large datasets, 3+ years building dashboards and visualizations in Tableau, Looker, or equivalent, 3+ years using Python or R for data manipulation and analysis, and 3+ years working with product analytics data.
• Skills: Expertise in interpreting data, extracting actionable insights, building and maintaining analytical assets, collaborating with business stakeholders, and communicating findings clearly to both technical and non-technical audiences.
• Bonus: Master’s or PhD in a quantitative or business field, working knowledge of product management processes and how data informs roadmap prioritization, proficiency in version control and collaborative documentation using GitHub, knowledge of statistical modeling including hypothesis testing and regression, and a track record of applying AI to real-world data analytics challenges.