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# Data Scientist - Insights and Analytics

- **Company:** Apple Inc.
- **Location:** Austin, TX, United States
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Airflow, Amazon Web Services, Data Analysis, Computer Engineering, D3.Js, Information Engineering, Data Transformation, Data Systems, Data Visualization, Data Warehousing, Python (Programming Language), NumPy, Cloud Services, Software Engineering, Large Language Models, Snowflake, Prompt Engineering, Apache Spark, Pandas, Scikit Learn, Information Technology, Data Analytics, Data Pipelines
- **Published:** August 7, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/data-scientist-insights-and-analytics-austin-tx-usa-58825854

## About the Role

end-to-end data lifecycle activities from data exploration to presentation of results * Collaborate with business stakeholders and platform teams to align analytics with business needs * Participate in business analytics projects through all phases including investigations, analysis, and storytelling Tasks * Coursework or project experience with scikit-learn or basic forecasting/statistical modeling * Familiarity with dbt, Apache Spark, or similar data transformation frameworks * Experience collaborating on team projects involving data quality or monitoring * Interest in prompt engineering or using LLMs for data analysis and automation workflows * Familiarity with JavaScript for data visualization (e.g., D3.js, Observable) is a plus * BS/BA in Computer Science, Software Engineering, Data Science, or equivalent degree * 1-3 years of experience in business analytics including surfacing insights and communicating findings * 1-3 years of experience with data pipelines, data modeling, or data
warehousing concepts in cloud platforms like AWS or Snowflake * Working proficiency in Python for data analysis and pipeline tasks (pandas, NumPy) * Exposure to cloud data platforms (AWS, Snowflake) and/or pipeline orchestration tools (Airflow, dbt) is a plus Key requirements *

## Description

Experteer Overview As a Data Scientist in Hardware Engineering, you bridge data engineering and business intelligence to power data-driven decisions. You will help architect data systems, deliver analytics, and translate outputs into actionable insights that inform strategic direction. Collaborating with senior team members and leadership, you'll support workforce planning, operations analytics, and high-impact projects across infrastructure and analytics. This role gives you exposure to the full data lifecycle on a cross-functional, distributed team. You will work to turn data into meaningful business outcomes and scalable solutions. Compensation / Benefits * Build and maintain data infrastructure to enable analytics and decision making * Deliver analytics and insights to inform strategic direction * Support workforce planning and operations analytics with senior team and leadership * Contribute to projects across pipeline development, data modeling, and data warehousing * Engage in end-to-end data lifecycle activities from data exploration to presentation of results * Collaborate with business stakeholders and platform teams to align analytics with business needs * Participate in business analytics projects through all phases including investigations, analysis, and storytelling Tasks * Coursework or project experience with scikit-learn or basic forecasting/statistical modeling * Familiarity with dbt, Apache Spark, or similar data transformation frameworks * Experience collaborating on team projects involving data quality or monitoring * Interest in prompt engineering or using LLMs for data analysis and automation workflows * Familiarity with JavaScript for data visualization (e.g., D3.js, Observable) is a plus * BS/BA in Computer Science, Software Engineering, Data Science, or equivalent degree * 1-3 years of experience in business analytics including surfacing insights and communicating findings * 1-3 years of experience with data pipelines, data modeling, or data warehousing concepts in cloud platforms like AWS or Snowflake * Working proficiency in Python for data analysis and pipeline tasks (pandas, NumPy) * Exposure to cloud data platforms (AWS, Snowflake) and/or pipeline orchestration tools (Airflow, dbt) is a plus Key requirements *


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