ML Data Scientist Manager - Ads Portfolio R&D

Job Description

Apple is forming a new Data Science Research team within Advertising Platforms to pioneer novel, data-driven strategies for managing and optimizing advertiser investments across the Apple Ads portfolio.

Requirements

• 3+ years of experience in data science, quantitative analysis, or a related field.
• 1+ years of experience in a formal management or team lead capacity.
• Strong background in quantitative finance, algorithmic trading, portfolio management, or econometrics.
• Deep understanding of statistical modeling, time-series analysis, and optimization techniques.
• Experience presenting complex technical concepts to both technical and non-technical stakeholders.
• Familiarity with the digital advertising landscape.

Responsibilities

• Lead, mentor, and grow a team of data scientists.
• Define the team's research vision and agenda.
• Guide quantitative research using advanced statistical and machine learning techniques.
• Develop frameworks for communicating the value of a portfolio-based approach to advertising.
• Collaborate with Sales, Product, and Data Insights teams to translate research findings into practical strategies.
• Engage with key clients to share research findings and establish Apple as a thought leader.
• Work with Privacy and Legal teams to ensure adherence to user privacy.
• Develop methods to track the impact of the team's research on advertiser behavior and performance.

Benefits

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.