Job Details

Job Information

data scientist
AWM-8638-data scientist
3/30/2026
4/4/2026
Negotiable
Permanent

Other Information

www.apple.com
Cupertino, CA, 95015, USA
Cupertino
California
United States
95015

Job Description

No Video Available
 

Weekly Hours: 40

Role Number: 200649923-0836

Summary

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.

Are you an enthusiastic Data Scientist eager to apply your expertise in a fast-paced, innovative tech environment? Join our Global Sourcing & Supply Management (GSSM) Solutions team and help drive data-informed decisions across our supply chain.

As a Data Scientist on our core AI/ML team, you will analyze complex datasets, develop predictive and statistical models, and deliver insights that inform strategy and product direction. You will collaborate closely with business stakeholders, product teams, and data engineers to translate ambiguous questions into structured analyses and practical data-driven solutions. Your work will support experimentation, forecasting, optimization, and measurable business impact across the supply chain.

If you enjoy exploring data to uncover patterns, testing hypotheses, and solving real-world business problems, we want to hear from you.

Description

  • Partner with business and product teams to identify high-impact analytical opportunities and translate ambiguous requirements into structured problem statements and measurable hypotheses
  • Design and develop predictive, statistical, and machine learning models to support forecasting, optimization, and decision-making
  • Conduct exploratory data analysis to uncover trends, anomalies, and performance drivers across supply chain workflows
  • Develop and evaluate modeling approaches using appropriate metrics, validation strategies, and experimentation frameworks (e.g., A/B testing, offline evaluation)
  • Build analytical and AI driven prototypes, including structured reasoning or Text-to-SQL workflows, to enable faster and more reliable access to insights
  • Communicate findings, assumptions, trade-offs, and limitations clearly to technical and non-technical stakeholders through visualizations, reports, and presentations
  • Collaborate with engineering teams to transition validated models into production, defining monitoring metrics and performance expectations
  • Stay current with emerging ML and GenAI techniques, prototype new approaches, and assess their applicability to supply chain challenges

Minimum Qualifications

  • Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field

  • 5+ years of industry experience in data science, analytics, or applied machine learning

Preferred Qualifications

  • MS or PhD in Statistics, Mathematics, Economics, Computer Science, Physics, or a related quantitative field

  • Strong statistical foundation, including hypothesis testing, experimental design, and model evaluation

  • Strong SQL skills with experience working on large-scale datasets

  • Proficiency in Python; experience with R is a plus

  • Experience with modern ML frameworks such as PyTorch or TensorFlow

  • Experience working with transformer-based models and large language models for analytical or workflow use cases

  • Practical experience using LLMs or GenAI models to support analysis, summarization, or decision workflows

  • Strong data visualization and storytelling skills

  • Experience applying ML or statistical models to forecasting, optimization, or operational decision-making problems

  • Experience in Supply Chain, Operations, or related domains

  • Ability to operate independently and influence cross-functional stakeholders

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .

Other Details

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