Applied ML Science Manager

Apple • Cupertino, CA

17h

About The Position

As an Applied ML Science Manager, you will have the responsibility of leading a highly talented team of scientists and engineers dedicated to pushing the boundaries of how Causal Inference and AIML can be leveraged to better serve our customers, focusing on Services such as Apple TV, Apple Music, Apple One, and the App Store. You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference solutions, that directly impact our products and provide a granular understanding of key business initiatives and marketing effectiveness. You will also be instrumental in defining the technical vision, strategy, and execution roadmap for our AIML initiatives, ensuring that we deliver high-quality, scalable, and impactful models that solve complex customer acquisition and engagement challenges. Beyond technical leadership, you will be a key driver in fostering a vibrant culture of innovation, continuous learning, and collaborative problem-solving within your team.

Requirements

• Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field
• 3+ years of experience in a leadership or management role, leading Applied Scientists, Machine Learning Engineers and Data Scientists
• 5+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist role
• Familiarity with a brand range of quasi-experimental Causal Inference techniques such as diff-in-diff, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, and propensity score matching
• Working knowledge of Marketing Mix models and validation through Matched Market testing
• Practical expertise leveraging Customer Lifetime Value models to drive business decision-making
• Solid understanding of AIML technologies including Generative AI
• Proven track record of successfully delivering complex projects from start to finish
• Proficiency in programming languages such as Python, R, SQL, Java, or C++
• Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices
• Excellent communication, collaboration, and presentation skills with meticulous attention to detail

Nice To Haves

• PhD in related field
• Hands-on experience leveraging Generative AI to improve productivity and generate new insights
• Curious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action

What This Job Offers

• Job Type: Full-time
• Career Level: Manager