Data Scientist - Business Process Re-Engineering

Apple Inc.; Austin (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Apple Inc. in Austin, TX, is seeking a Data Scientist to design and deliver end-to-end analytics solutions for business processes within Operations and Supply Chain.

You will work with GenAI, agentic AI, and modern data science methods to translate complex data into actionable insights for leadership. The role focuses on building scalable models, dashboards, and tools, collaborating with data engineers, and continuously refining solutions to meet evolving supply chain needs, with an emphasis on

Qualifications

• PhD in Computer Science, Statistics, Applied Math, Data Science, Operations Research or related field, with 5+ years of industry experience
• Forecasting, optimization, or simulation experience within supply chain or operations
• Ability to work in a fast-paced, iterative environment and deliver under deadlines
• Proven experience building and deploying large-scale data science models with MLOps practices, including CI/CD workflows
• Experience prototyping, developing software in Python and SQL, and leveraging data visualization tools

Responsibilities

• Engage with business teams to identify opportunities and translate requirements into technical solutions
• Design and architect end-to-end data science solutions for complex supply chain problems
• Collaborate with data engineers to implement robust, production-ready models
• Continuously monitor and evolve deployed solutions with feedback loops and agility
• Present key findings to leadership in non-technical terms to drive decisions
• Research and evaluate emerging technologies (GenAI, agentic AI, visualization tools) to expand capabilities

Job description

Data Scientist - Business Process Re-Engineering

Austin, Texas, United States Operations and Supply Chain

Apple is where extraordinary people do their best work. If making a real impact excites you, a career here might be your dream — just be prepared to dream big!Apple's growing supply chain complexity demands innovative approaches beyond traditional analytics. You'll join a team designing and developing advanced analytics solutions using GenAI, Agentic AI, and modern data science methods to drive decisions. You're passionate about turning data into impactful insights, staying ahead of technology trends, and thrive navigating ambiguity in a fast‑paced environment. If this sounds like you, we'd love to talk.

Description

Engage with business teams to identify opportunities through in depth conversations and being able to translate those requirements into technical solutions and drive critical projectsDesign and architect end‑to‑end data science solutions—selecting from established techniques or engineering novel algorithms tailored to complex supply chain business problemsCollaborate with data engineers and infrastructure partners to implement robust solutions and operationalize models.Continuously enhance and evolve deployed solutions through monitoring, feedback loops, and iteration to meet changing business needs with agilityPresent key findings to leadership to evaluate business impact, in non‑technical termsResearch and evaluate emerging technologies—including GenAI, agentic frameworks, and advanced visualization tools—to expand the team's technical capabilities and accelerate innovationChampion a culture of experimentation and continuous learning, bringing innovative and strategic thinking to reporting, business analytics, and AI‑powered automationDevelop custom models, algorithms, and interactive visualizations—including dashboards and self‑service tools—to deliver actionable Supply Chain insights at scaleWrangle and analyze data to identify patterns, trends, and feature engineeringDefine and track key performance metrics to quantify the business value of deployed data science solutions

Minimum Qualifications

• PhD in Computer Science, Statistics, Applied Math, Data Science, Operations Research or a related field and 5+ years of industry experience OR MS in related field with 8+ years hands‑on industry experience
• Demonstrated experience in forecasting, optimization, or simulation within supply chain or operations domains
• Ability to work well in a fast‑paced, iterative environment and deliver projects under timeline pressures
• Proven experience building and deploying large‑scale data science and machine learning models, including anomaly detection, NLP, and deep learning techniques with MLOps practices, model versioning, and CI/CD pipelines for implementing, deploying and managing production AIML workflows and projects
• Experience prototyping and developing software in programming languages (Python, etc.) as well as leveraging advanced SQL for data manipulation
• Experience building out scalable solutions using GenAI technologies with an emphasis on Agentic solutions using MCP servers, agents, and skills
• Experience with data acquisition tools (e.g. SQL), data mining and data visualization. Strong background in AIML libraries and frameworks such as Scikit Learn, TensorFlow, PyTorch
• Experience prototyping, developing software and implementing data science pipelines and applications in programming languages (Python/Java/C++)
• Track record of staying current with industry best practices, rapidly adopting emerging technologies (e.g., LLMs, RAG, vector databases), and building functional prototypes to validate concepts
• Champion a culture of experimentation and continuous learning, bringing innovative and strategic thinking to reporting, business analytics, and AI‑powered automation
• Proven ability to own and deliver end‑to‑end projects from scoping through deployment and post‑launch iteration
• Proficiency with cloud data platforms (e.g., Snowflake), relational databases (e.g., MySQL), interactive front‑end frameworks (e.g., Streamlit, Tableau, ThoughtSpot), and containerization/orchestration tools (Docker, Kubernetes)
• Working knowledge of predictive modeling and classification algorithms, regression, clustering, and anomaly detection
• Passionate about understanding and solving problems and exceptional ability to translate complex AI and ML concepts into clear business narratives, with a talent for data storytelling and presenting analysis effectively to influence senior leadership and cross‑functional partners
• Self‑sufficient with an ability to thrive in an environment of autonomy amidst ambiguity
• Strong interpersonal and collaboration skills to partner effectively across functions, share knowledge, communicate findings, and integrate diverse feedback

Preferred Qualifications

• Meticulous attention to detail, data integrity, and data wrangling
• Ability to get things done, experience in delivering end‑to‑end projects
• High intellectual curiosity to learn and understand business needs
• Self‑sufficient with an ability to thrive in an environment of autonomy amidst ambiguity
• Strong interpersonal and collaboration skills to partner effectively across functions, share knowledge, communicate findings, and integrate diverse feedback

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

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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Apple accepts applications to this posting on an ongoing basis.