Diagnostics Insights Analyst: Data Science for Quality

Apple; Jefferson City (MO); On-site; USD 28,000 - 41,000; Full time

Job summary

Apple is seeking a Diagnostics Insights Analyst to transform real-world data into actionable insights that improve product quality and customer experiences. You will work with Snowflake SQL, Python and Tableau to build dashboards, data pipelines, and models supporting Mac and audio product analysis.

You will collaborate with engineers and cross-functional teams to identify data opportunities, present findings to diverse audiences, and drive data‑driven decisions across the organization.

Qualifications

• 2+ years of data analysis experience in a professional setting.
• Advanced proficiency in Snowflake SQL.
• Strong Tableau experience with dashboard deployment.
• Expertise in Python for data processing and modeling.
• Experience with large data pipelines (Spark, Hive) is a plus.
• Excellent cross‑functional communication abilities.

Responsibilities

• Collaborate with project engineers to identify data analysis issues and opportunities.
• Create and maintain dashboards using SQL, Tableau and Python.
• Develop and optimize data pipelines for reliable analysis.
• Ensure data consistency and accuracy across assets with attention to detail.
• Extract valuable insights from big data and present them to diverse audiences.
• Develop algorithms to automate data cleaning, analysis and modeling.
• Contribute to planning and forecasting to address uncertainty in projects.

Skills

Data analysis

Snowflake SQL

Tableau

Python

Communication

Collaboration

Education

Bachelor's Degree

Tools

Spark

Hive

Job description

Apple is seeking a Diagnostics Insights Analyst to transform real-world data into actionable insights that improve product quality and customer experiences. You will work with Snowflake SQL, Python and Tableau to build dashboards, data pipelines, and models supporting Mac and audio product analysis.

You will collaborate with engineers and cross-functional teams to identify data opportunities, present findings to diverse audiences, and drive data‑driven decisions across the organization.