Senior Data Scientist for NLP & LLM Analytics

Apple Inc.; Cupertino, Northern (CA, KY); Hybrid; USD 150,000 - 278,000; Full time

Job summary

Apple is seeking a Sr Data Scientist in Cupertino, California, to advance the online metrics and insights for Apple AI products. You will apply statistical and language data analysis, leverage LLMs, and collaborate with engineering and product teams to deliver measurable improvements while upholding privacy—contributing to user experiences across features like Siri and Search.

The role emphasizes building robust analytics pipelines, designing experiments, and translating insights into product

Qualifications

• 3+ years of data science experience applying quantitative methods to structured and unstructured data.
• Strong programming skills in Python and SQL, with experience in data manipulation, processing, and analytics pipelines.
• Experience with LLM-driven analytics workflows, using Python coding frameworks and evaluation pipelines.

Responsibilities

• Use statistical and LLM analysis of structured and linguistic data to deepen our understanding of Apple’s AI product.
• Investigate worldwide product usage to identify weaknesses and opportunities to improve the product.
• Define metrics and instrumentation strategies to assess the success of new features.
• Build relationships with Engineering leads and product partners to drive a privacy-first strategy for analytical insight.

Skills

Python

SQL

LLM analytics

A/B testing

Statistical analysis

Education

Master's degree

PhD preferred

Tools

Python frameworks

Job description

Apple is seeking a Sr Data Scientist in Cupertino, California, to advance the online metrics and insights for Apple AI products. You will apply statistical and language data analysis, leverage LLMs, and collaborate with engineering and product teams to deliver measurable improvements while upholding privacy—contributing to user experiences across features like Siri and Search.

The role emphasizes building robust analytics pipelines, designing experiments, and translating insights into product