Senior Machine Learning Data Scientist Manager - Apple Ads (Cupertino)

Senior Machine Learning Data Scientist Manager - Apple Ads

Cupertino, California, United States Software and Services

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 dataacting 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 Apples 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

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 $228,100 and $393,800, 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 Apples 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 Apples Employee Stock Purchase Plan. Youll 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.

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 .

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