Description

Description

In this role, you are responsible for designing and building the next generation algorithms for core auction system that powers our advertising platform to drive optimal outcomes for advertisers, users, and our platform. You will have the opportunity to build the next generation solutions for marketplace optimization that enable driving optimal value for multiple stakeholders in the system. You will be a thought expert and a domain expert guiding teams for building the next generation solutions for marketplace optimization. You will work with a variety of cross functional business partners to set strategy and bring end-to-end solutions that scale as we grown. You will have the opportunity to apply your ability to move the state of the art techniques in a fast growing business that positively impacts publishers, developers and Apple users at global scale.

Minimum Qualifications

• 10+ years of experience working in online advertising and marketplace design
• Domain expert in ads auction design, budget and bid optimization is a must
• Experience in auction theory, mechanism design, optimization, statistics, machine learning, quantitative methods, control systems, or reinforcement learning
• Ability to apply and implement research concepts, ultimately in production quality code
• Experience defining clear, testable research hypotheses, including intended impact on the business
• Deep knowledge of design of experiments, online experimentation approaches, preferably at scale
• Ability to formulate and advocate for R&D objectives and results to cross-functional team members including executive business leadership and product management
• Experience contributing and/or reviewing research for top conferences and publications
• Deep fluency in Java or Python
• Experience with Spark, Hadoop or other distributed frameworks
• MS in Economics, Operations Research, Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry

Preferred Qualifications

• PhD in Economics, Operations Research, Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry

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 $212,000 and $386,300, 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.

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 .