Data Scientist, Business Process Re-Engineering

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Austin, TX
Posted
148 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $156k
$87k most similar roles pay here $214k

This listing doesn't post a salary. Most similar roles pay $126,800–$184,900.

Based on 240 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Data Scientist, Business Process Re-Engineering

The Data Scientist - Business Process Re-Engineering joins the Operations and Supply Chain team to address growing supply chain complexity through advanced analytics. This role involves engaging with business teams to translate requirements into technical solutions, designing end-to-end data science architectures, and developing custom models, algorithms, and interactive visualizations like dashboards for actionable insights. The candidate will build and deploy large-scale machine learning models involving anomaly detection, NLP, and deep learning while utilizing MLOps practices, CI/CD pipelines, and containerization tools like Docker and Kubernetes. Key technologies include Python, Java, C++, SQL, Snowflake, MySQL, Scikit Learn, TensorFlow, PyTorch, and GenAI frameworks featuring agentic solutions with MCP servers. The role focuses on solving complex supply chain problems by leveraging emerging technologies such as LLMs, RAG, vector databases, and advanced visualization tools like Tableau or ThoughtSpot.

What does a Data Scientist earn?

Median $162025 from 276 postings across 61 companies.

See salary data

What you'll do

  • Translate business requirements from supply chain teams into technical data science solutions.
  • Design and architect end-to-end data science solutions using custom algorithms and advanced analytics.
  • Develop and deploy large-scale machine learning models including anomaly detection, NLP, and deep learning.
  • Build scalable solutions utilizing GenAI technologies and agentic frameworks to automate business processes.
  • Create interactive visualizations and self-service dashboards to provide actionable supply chain insights.
  • Research and prototype emerging technologies like LLMs, RAG, and vector databases to expand technical capabilities.
  • Monitor and iterate on deployed models to ensure they meet evolving business needs.
  • Present complex data findings and business impacts to senior leadership in non-technical terms.

What we're looking for

  • PhD in Computer Science, Statistics, Applied Math, Data Science, Operations Research, or a related field and 5+ years of industry experience.
  • MS in a related field with 8+ years of hands-on industry experience.
  • Experience in forecasting, optimization, or simulation within supply chain or operations domains.
  • Proven experience building and deploying large-scale ML models using MLOps practices, model versioning, and CI/CD pipelines.
  • Proficiency in programming languages such as Python, Java, or C++, and advanced SQL for data manipulation.
  • Experience building scalable solutions using GenAI technologies with an emphasis on Agentic solutions.
  • Expertise in AI/ML libraries (Scikit Learn, TensorFlow, PyTorch) and cloud platforms like Snowflake.
  • Ability to translate complex technical concepts into clear business narratives for senior leadership.

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