Machine Learning Engineer - People Analytics

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$181,100–$272,100 / yr
Posted
today

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $221k
This role $227k
$160k most similar roles pay here $284k

This role pays more than 61% of similar roles. Most pay $192,250–$249,750 — the shaded band above. At the midpoint, this role pays about $227k versus about $221k for comparable roles.

Based on 240 similar postings.

Employer

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 1777 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1443 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer - People Analytics

Join Apple's People Analytics Team as a Machine Learning Engineer and contribute to crafting predictive models and analytical solutions that enhance talent management, employee surveys, compensation, and recruiting. You will collaborate closely with data engineers and system architects to implement real-time and batch decisioning solutions in production environments while ensuring the operational health of these systems. Key responsibilities include designing custom algorithms for classification, regression, clustering, and anomaly detection, developing metrics to measure solution performance, and researching new technologies to enhance team capabilities. The role requires proficiency in Python or R, SQL, and experience with natural language processing and network analysis. This position presents unique challenges due to Apple's commitment to privacy and the scale of its operations, offering opportunities to innovate within a human-centric framework.

What you'll do

  • Design machine learning approaches and custom algorithms to solve business problems.
  • Implement real-time and batch decisioning solutions in collaboration with engineers.
  • Monitor production decision points to ensure operational and metric health.
  • Develop performance metrics for analytics solutions and communicate results effectively.
  • Research new technologies and methods to enhance team’s technical capabilities.

What we're looking for

  • MS degree and 5+ years of applying data science to real-world business problems.
  • Expertise in classification, regression, clustering, and anomaly detection algorithms.
  • Proficiency in SQL for database joins and analytical functions.
  • Experience implementing data science pipelines using Python or R.
  • Background in employee data analysis or HR systems.
  • Knowledge of natural language processing techniques is beneficial.
  • Skill in translating business processes into analytic solutions effectively.

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