Data Scientist - Business Process Re-Engineering

Apple, Inc.; Austin (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Apple Inc. in Austin, Texas, is seeking a Data Scientist - Business Process Re-Engineering to design GenAI/LLM-powered applications for the supply chain.

You will collaborate with data engineers, build production-quality solutions, and integrate LLM APIs (LangChain, LangGraph) with dashboards to drive actionable insights. This role emphasizes experimentation, rapid prototyping, and translating complex analytics into business impact for leadership, while staying ahead of technology trends in a

Qualifications

• PhD or MS with extensive hands-on experience in AI/ML and software engineering.
• Experience building end-to-end GenAI/LLM-powered applications and APIs.
• Strong background with MLOps, model versioning, and deployment practices.

Responsibilities

• Design and architect GenAI/LLM-powered applications and agent workflows.
• Engage with business teams to translate requirements into technical solutions.
• Integrate LLM APIs/frameworks and operationalize robust solutions.
• Present findings to leadership in non-technical terms and track business impact.

Skills

End-to-end application development

RESTful APIs

Frontend technologies

Education

PhD in CS/Software Eng/Statistics/Applied Math/Data Science/OR or related field

MS in related field with 8+ years hands-on industry experience

Tools

FastAPI

React

Streamlit

Docker

Kubernetes

CI/CD

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. Apple's growing supply chain complexity demands innovative approaches beyond traditional analytics. You'll join a team designing and building functional GenAI/LLM-powered applications and agent workflows, alongside 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.

Description

Design and architect end-to-end GenAI/LLM-powered applications and agent workflows, adapting and orchestrating pre-trained foundation models, tailored to complex supply chain business problemsEngage with business teams to identify opportunities through conversations and translating requirements into technical solutions to drive critical projectsCollaborate with data engineers and infrastructure partners to integrate LLM APIs and frameworks (e.g., LangChain, LangGraph) and operationalize robust solutionsBuild production quality solutions or enhance and evolve deployed solutions through engineering, evals, 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, software engineering, 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 automationBuild RAG pipelines and vector search capabilities, along with 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 AI solutions

Minimum Qualifications

• PhD in Computer Science, Computer Software Engineering, 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
• Experience developing end-to-end applications, including backend services and RESTful APIs (e.g., FastAPI) and interactive front-ends (e.g., React, Streamlit)
• Proven experience building and deploying production GenAI/LLM-powered applications and machine learning models on cloud platforms (e.g., AWS, GCP, Azure), with MLOps practices, model versioning, CI/CD pipelines, containerization/orchestration (Docker, Kubernetes), and monitoring to deliver scalable, reliable services
• Hands-on experience integrating LLM APIs (e.g., OpenAI, Anthropic) and frameworks (e.g., LangChain, LangGraph) to build scalable agentic solutions using MCP servers, agents, and skills
• Expertise in software engineering and designing evals to measure LLM output quality, accuracy, and reliability
• Strong background in AIML libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and predictive modeling techniques, including classification, regression, clustering, and anomaly detection
• Demonstrated experience in forecasting, optimization, or simulation within supply chain or operations domains
• Proven ability to own projects end-to-end, from scoping and rapid prototyping through deployment and post-launch iteration, while staying current with emerging technologies (e.g., new foundation models, agent frameworks)

Preferred Qualifications

• Experience designing and maintaining scalable data pipelines (ETL/ELT, batch and streaming; e.g., Airflow, Spark, dbt) on cloud data platforms (e.g., Snowflake) and relational databases (e.g., MySQL), with meticulous attention to data quality and integrity, and surfacing insights through BI tools (e.g., Tableau, ThoughtSpot)
• Experience building Retrieval-Augmented Generation (RAG) and vector search solutions using vector databases
• Experience adapting and orchestrating pre-trained foundation models (e.g., tool use, multi-agent orchestration)
• Exceptional ability to translate complex AI/ML concepts into clear business narratives and influence senior leadership, with strong collaboration skills to partner across functions and integrate diverse feedback
• Self-sufficient, intellectually curious, and biased toward action, thriving amid autonomy, ambiguity, and timeline pressure in a fast-paced, iterative environment

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

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