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At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for while enabling advertisers to grow their businesses.
Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is grounded in trust, connection, and impact. We respect user privacy, thoughtfully integrate advertising into the customer experience, and deliver value for advertisers of all sizes, from small app developers to global brands. When advertising is done right, it benefits everyone.
Within Apple Ads, the Search Demand Product Analytics team is growing and looking to add a Manager to the leadership team. This role will lead the Advertiser Measurement function, partnering closely with Search Demand Product to support new product development, launch measurement, and impact evaluation. The team works across opportunity sizing, telemetry and measurement design, launch reporting, and post-launch analysis to ensure product decisions are grounded in rigorous, scalable analytics.
This role will build, lead, and mentor a team of data scientists while helping formalize processes that scale with increasing product velocity.
Description:
As a Manager on the Apple Ads Search Demand Product Analytics team, you will lead a group of data scientists responsible for advertiser measurement and new product analytics. Your team will support the full product lifecycle, including opportunity sizing, defining measurement and telemetry requirements, designing launch reporting, and evaluating post-launch impact.
You will set priorities, raise the level of analytical rigor, and ensure strong cross-functional alignment with Product and Engineering stakeholders. As the organization grows, you will help establish scalable measurement frameworks that enable consistent, high-quality decision-making across launches.
This is a hands-on leadership role. The Manager is expected to operate with the technical depth of a senior individual contributor while leading and developing others.","responsibilities":"Collaborate with Product Insights Leadership: Work closely with Product Insights leadership to provide timely insights on our product, identify opportunities for new or improvements to existing products and consistently deliver actionable, innovative and accurate product analysis.
Lead, Mentor, and Grow: Build and manage a team of early-to-mid-career data scientists, fostering a culture of rigorous analysis, innovation, and intellectual curiosity.
Collaborate with Product Teams: Drive timely and impactful insights and analysis in product areas included but not limited to: Measurement & Telemetry, API & UI instrumentation, Campaign Management, Demand Side Experimentation, Reporting and Insights, Policy & Compliance, and Bidding.
Product Impact: Guide the team in leveraging advanced statistical and machine learning techniques to provide innovative and actionable product insights that improve the product for our customers
Partner with Product, Engineering, and GTM Teams: Collaborate closely with stakeholders from Product, Engineering and GTM teams to insure high quality, actionable insights are provided throughout the GTM process.
Champion Privacy: Work with Privacy and Legal teams to ensure all analysis and data usage adheres to Apple's strict commitment to user privacy.
Measure Impact: Develop methods to track the influence and adoption of the team's work on our business.
Minimal travel required. This role is ideal for a technically strong data science leader who is passionate about developing people and driving measurable product impact.
Preferred Qualifications:
Experience in digital advertising, search ads, marketplaces, or performance-driven consumer businesses
Familiarity with mobile app marketing or auction-based systems
Experience designing scalable measurement frameworks for new product launches
Experience building reporting systems that inform leadership decision-making
Track record of influencing product strategy through data-driven insights
Experience working in privacy-conscious environments
Minimum Qualifications:
5+ years of experience in product analytics, data science, or a related quantitative field
Experience leading or mentoring data scientists, with demonstrated technical and project leadership
Strong foundation in experimentation, statistical analysis, and business impact measurement
Ability to operate with senior-level technical depth and guide complex analytical work
Experience partnering cross-functionally with Product and Engineering teams
Excellent communication skills, with the ability to translate complex analysis into clear, actionable insights
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 .
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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Junior/L3 · Specialist
4,913 reports
$61,616
total / year
Base
$61,616
Stock
-
Bonus
-
$41,521
$91,436
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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