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Salary
≈ $56k – $160k per year (Estimated)
Location
In office (Shanghai)
Seniority
Staff

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 14, 2026. Apple scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Apple is an American multinational technology company founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne, and headquartered in Cupertino, California. It designs and sells consumer hardware including the iPhone, Mac, iPad, Apple Watch, AirPods and Vision Pro, together with the operating systems and silicon that run them. A growing services division built around the App Store, iCloud, Apple Music, Apple TV+ and Apple Pay now contributes a large share of profit, making Apple one of the most valuable companies in the world.

Apple's Strategic Data Solutions (SDS) team is looking for a talented manager who is passionate about leading a team of data scientists that craft, implement, and operate analytical solutions with direct and measurable impact to Apple and its customers.

You will build and lead a team of SDS machine learning engineers, who employ machine learning, statistical analysis techniques, and system design to build end-to-end solutions across Apple's business operations.

You will engage with a large and talented cross-functional team as we work to build out our data-driven programs. Apple's dedication to customer privacy, the adversarial nature of risk, and the enormous scale of the business present exciting challenges to traditional machine learning and data science techniques. On this team, you will push the limits of integrating existing machine learning methods with engineering and business process to deliver tangible value.

Description

Lead and mentor a team of software developers and machine learning engineers

Design and maintain real-time automated decisioning systems and operations for financial products

Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions

Engage with business partners and understand their unique requirements and design technical solutions

Review the team's production code and logic for highly integrated systems

Distill and clearly communicate complex technical topics for both business and engineering stakeholders

Analyze data and tell meaningful stories to assist business partners

Minimum Qualifications

(DO NOT POST AND WILL UPDATE)

Experience leading a team of machine learning engineers

Practical experience training, deploying, and maintaining decisioning algorithms

Familiarity with distributed databases, data warehousing, and SQL

Ability to implement custom real-time or batch machine learning applications with their appropriate data pipelines

Ability to comprehend and debug complex system integrations spanning toolchains and teams

Ability to extract meaningful business insights from data and identify the stories behind the patterns

Ability to think at a systems level to anticipate technical, business, and customer impact

Clear communication and presentation skills

Excellent problem solving skills, business acumen, and solution design mentality

Experience writing, reviewing, and deploying production software

Graduate degree in a quantitative field or equivalent professional experience

Experience in the following a plus: payments, finance, or financial risk

Preferred Qualifications

(DO NOT POST AND WILL UPDATE)

Experience leading a team of machine learning engineers

Practical experience training, deploying, and maintaining decisioning algorithms

Familiarity with distributed databases, data warehousing, and SQL

Ability to implement custom real-time or batch machine learning applications with their appropriate data pipelines

Ability to comprehend and debug complex system integrations spanning toolchains and teams

Ability to extract meaningful business insights from data and identify the stories behind the patterns

Ability to think at a systems level to anticipate technical, business, and customer impact

Clear communication and presentation skills

Excellent problem solving skills, business acumen, and solution design mentality

Experience writing, reviewing, and deploying production software

Graduate degree in a quantitative field or equivalent professional experience

Experience in the following a plus: payments, finance, or financial risk

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