Skip to content

Open nowPosted yesterday

Data Scientist - Business Process Re-Engineering

Apple6,518 open roles

Where
Austin, United States of America
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowData Scientist - Business Process Re-EngineeringApple · Austin, United States of America
  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Apple's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. Apple postings stay open a median of 47 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: posted yesterday

Apple median: 47 days open

The posting

Summary

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 problems Engage with business teams to identify opportunities through conversations and translating requirements into technical solutions to drive critical projects Collaborate with data engineers and infrastructure partners to integrate LLM APIs and frameworks (e.g., LangChain, LangGraph) and operationalize robust solutions Build production quality solutions or enhance and evolve deployed solutions through engineering, evals, monitoring, feedback loops, and iteration to meet changing business needs with agility Present key findings to leadership to evaluate business impact, in non-technical terms Research and evaluate emerging technologies, including GenAI, agentic frameworks, software engineering, and advanced visualization tools, to expand the team's technical capabilities and accelerate innovation Champion a culture of experimentation and continuous learning, bringing innovative and strategic thinking to reporting, business analytics, and AI-powered automation Build RAG pipelines and vector search capabilities, along with interactive visualizations, including dashboards and self-service tools, to deliver actionable Supply Chain insights at scale Wrangle and analyze data to identify patterns, trends, and feature engineering Define 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 Strong software engineering fundamentals (data structures, algorithms, system design) with production-quality coding in Python and TypeScript/JavaScript and advanced SQL, following best practices in version control (Git), code review, testing, and documentation 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

EEO Statement

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

Accessibility

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.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Application Deadline

Apple accepts applications to this posting on an ongoing basis.

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Apple's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.
  3. We apply on Apple's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.
  4. Every reply, sorted

    Apple's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.
  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.