Data Scientist / Senior Data Scientist, Software Engineering

At Apple, you'll accomplish truly phenomenal things. The SWE Data Science team analyzes and produces insights from diagnostic and usage data from hundreds of millions of devices all over the world. We collaborate with teams across Apple including Engineering, Product, Marketing and Finance to solve challenges and improve the user experience.

We are looking for an ambitious data scientist that is excited to work with large, complex datasets and shape the future direction of our products.

Description

As a data scientist on the SWE Data Science team, you will use data to drive product decisions and improvements. You will apply quantitative methods and statistical techniques to conduct exploratory data analysis, define new metrics, create compelling data visualizations, and develop analytical frameworks that translate raw data into actionable software development opportunities. You will own the analytical process end-to-end, from architecting and designing scalable and efficient data processing pipelines to conducting deep dive analyses and communicating the results. You will also explore new opportunities to innovate with GenAI and LLMs to accelerate our team's velocity and impact.

We are a fast-paced and high-functioning team of data scientists that use the latest Big Data technologies and GenAI to tackle complex, large-scale problems using immense quantities of collected data. This team works closely with core operating systems (iOS, macOS, iPadOS, watchOS and visionOS), application development, and other cross-functional teams across Apple's platforms. The ideal candidate has a strong technical background and is excited to work on a collaborative and innovative team.","responsibilities":"Design and own the foundational datasets, visualizations and reports for Apple's leadership that communicate a cohesive narrative about our core operating systems (iOS, iPadOS, macOS, watchOS and visionOS).

Develop robust and scalable metrics frameworks, data pipelines, and comprehensive reporting to measure the health and performance of Apple's products and features.

Partner with Engineering to design and implement new telemetry while prioritizing user privacy.

Build relationships with cross-functional partners in Engineering, Product and Marketing to identify data-driven insights and opportunities to inform product decisions and improve the user experience.

Define and lead rigorous and innovative analyses to deepen our understanding of our software and products.

Innovate and transform the way in which our team works - explore new opportunities to leverage Generative AI and new technologies to optimize Data Science workflows and scale the impact of our team.

Preferred Qualifications

Experience with LLM-driven workflows or leveraging GenAI to augment and improve Data Science workflows.

Experience designing and building scalable data systems and pipelines to support complex, large-scale analytics initiatives.

Strong product mindset and commitment to improving the user experience.

Minimum Qualifications

Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Economics) or equivalent professional experience.

Strong proficiency in SQL and at least one programming language, such as Python or R, and experience with data visualization platforms (e.g. Tableau, Looker).

3+ years of data science or related experience, preferably in a consumer tech company.

Strong fundamentals in data engineering, product analytics, statistics, and machine learning.

Experience with distributed computing frameworks like Spark, Hadoop or Flink.

Excellent interpersonal and communication skills, with the ability to collaborate effectively with both technical and non-technical teams.

Self-motivated and intellectually curious, with a demonstrated ability to thrive in ambiguous problem spaces.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .