Machine Learning Manager - Apple Ads
Cupertino, California, United States
Software and Services
Summary
Posted: May 14, 2025
Weekly Hours: 40
Role Number: 200601255
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 and helping advertisers 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 designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone!
The Data Insights team within Apple Ads is seeking a bright and endlessly curious data expert to lead our Core Insights team that supports the organization. This individual will be responsible for leading a team that turns the huge amounts of data generated by user searches, app metadata, and App Store content into business insights that improve the customer experience for the end-user as well as drive discovery and productivity for app developers.
We are seeking a self-motivated leader that can execute on near-term plans and contribute to defining a longer-term vision for our team and Apple Ads. This role involves working with internet-scale data across numerous product and customer touch points; undertaking in-depth, quantitative analysis on business performance; developing and running prediction and forecasting models; and building ML models including LLMs to drive core business decisions.
The team's culture is focused on rapid iteration with open feedback and debate along the way, plus strong collaboration with product, engineering, business, and marketing partners.
You will have experience hiring and leading large-scale, sophisticated data science teams that deliver impactful insights via pattern mining, anomaly detection, modeling, classification, and creation of wide ranging analytical tooling. Successful candidates will take pride in implementing and sustaining end-to-end analytical solutions that have direct and measurable impact. The role requires both a broad knowledge of existing data mining algorithms and creativity to invent and customize when necessary.
Description
Apply best-in-class modeling and analytics techniques to enable rapid insights discovery for multiple business, cross-functional teams and senior leadership
Lead development of all predictive models on seasonality, anomaly detection, forecasting metrics for all ad businesses. Guide end-to-end lifecycle stages from PoC development, testing, industrialization and monitoring model performance.
Lead classification and categorization of queries, apps, and discovery of app cohorts using ML models/ LLMs. Extract @contextual signals from aggregated interaction data to feed into ads marketplace design.
Lead analysis of business metrics, their interactions, and framework design on deep-dive investigations. Monitor usage metrics, provide business-based explanations for large-scale trends and patterns.
Lead creation of self-serve, analytics tools and data products to enable insights discovery at lightning speed and scale.
Automate and scale existing analysis methods. Institute new approaches on modeling and analysis frameworks.
Guide statistical analysis, model development and visualization of data to help understand how advertisers use Apple Ads for app promotion.
Support a wide variety of stakeholders ranging from sales, finance, product, engineering, and senior leadership. Frequently present insights to senior leaders and be able to distill findings into clear, comprehensible, and actionable insights.
Lead a team of multiple managers and ICs. Hire and develop leading talent with proven, relevant, data science skills. Motivate and ensure success for the team by defining roles and responsibilities that are clearly communicated, define and share a strategic vision for the function, establish processes, and develop personal development plans.
Empower global business teams with insights to inform and fulfill strategic objectives and goals.
Minimum Qualifications
10+ years of experience leading data science, machine learning teams including managing managers.
2+ years of experience in digital advertising and performance-based platforms.
Experience in advanced quantitative methods and model development with a strong focus in exploratory data science. Must include experience with regression, classification, clustering, time-series analysis and LLMs.
Experience working with modern data engineering technologies and cloud-based data warehousing solutions. Familiarity with database modeling and data warehousing principles.
Well-rounded individual with hands-on experience in writing code to query and transform both unstructured and structured data-acting as a mentor to your team while not afraid to dig in and get your hands dirty.
Programming skills in Python and SQL. Comfort with advanced analytics and data visualization tools and libraries such as Pandas, R, Spark, and Tableau.
Must be able to guide and lead analysis across teams of ML data scientists and data engineers. Seamlessly collaborate with a wide range of stakeholders including senior leadership, product managers, finance, engineering.
Have a strategic mindset with an aptitude to condense complex concepts, analysis, and models into actionable data driven solutions and strategies that will propel Apple's digital advertising businesses.
Demonstrated business acumen; ability to understand and anticipate the decisions stakeholders must make supported by data. Ability to produce and communicate data insights that translate into meaningful business impact.
Excellent communication, collaboration, stakeholder management, and planning skills; demonstrated success building buy-in for an innovative and bold vision.
Ability to work effectively with engineering partners to meet the data needs of the business, translating business needs into analytical requirements.
Deep knowledge and experience in digital, performance-based advertising platforms.
Bachelors, or equivalent experience in a quantitative field, such as Engineering, Computer Science, Applied Mathematics, Econometrics, Operations Research, Social Sciences, Statistics, or equivalent professional experience
Preferred Qualifications
15 years of experience leading data science, machine learning teams including managing managers. 5+ years of experience in digital advertising and performance-based platforms.
5+ years of experience in digital advertising and performance-based platforms.
Ph.D. or equivalent experience in a quantitative field, such as Engineering, Computer Science, Applied Mathematics, Econometrics, Operations Research, Social Sciences, Statistics, or equivalent professional experience
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $190,700 and $329,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.Learn more about Apple Benefits. (https://www.apple.com/careers/us/benefits.html)
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\EEOC\KnowYourRights6.12ScreenRdr.pdf) .
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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088\EEOC\KnowYourRights6.12ScreenRdr.pdf) .
Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.
Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program (https://www.apple.com/jobs/pdf/EverifyPosterEnglish.pdf) .
Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .
Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .
Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you're applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
