Data Scientist, Decision Intelligence for AI‑Driven Sales

Apple Inc.; Northern (KY); Hybrid; USD 145,000 - 218,000; Full time

Job summary

Apple Inc. is seeking a Data Scientist for the US Decision Intelligence team in Cupertino, CA.

You will craft predictive models, build end-to-end insight pipelines, and deploy LLM-powered solutions to empower Apple’s sales force and partners. The role emphasizes translating business problems into technical solutions, partnering with data engineers, software developers, and business stakeholders, and delivering measurable improvements across regions and tools.

Qualifications

• 4+ years in data science, data analysis, or data visualization.
• Experience with LLMs, RAG architectures, and prompt engineering.
• Proficient in Python and ML/data science libraries.
• Strong SQL skills and experience with cloud data platforms (Snowflake, Spark, BigQuery).
• Experience with data visualization tools (Tableau, Plotly, d3).
• Familiarity with Git and deployment frameworks (Docker, Kubernetes).

Responsibilities

• Lead end-to-end insight development from data prep to deployment.
• Design and deploy ML models for forecasting and anomaly detection.
• Build RCA and recommendation engines to enhance insights and chatbots.
• Evaluate LLMs and establish pipelines for model monitoring and latency control.
• Collaborate with AI engineers, PMs, and stakeholders to scale features across regions.

Skills

LLMs

Python

SQL

Data Visualization

Git

Docker

Time Series

Education

Bachelor’s degree in Computer Science or related

Tools

Snowflake

BigQuery

Tableau / Tableau Server

Kubernetes

Job description

Apple Inc. is seeking a Data Scientist for the US Decision Intelligence team in Cupertino, CA.

You will craft predictive models, build end-to-end insight pipelines, and deploy LLM-powered solutions to empower Apple’s sales force and partners. The role emphasizes translating business problems into technical solutions, partnering with data engineers, software developers, and business stakeholders, and delivering measurable improvements across regions and tools.