Applied ML Science Manager

Services at Apple help hundreds of millions of customers get the most out of the devices they love through amazing apps award-winning shows and movies immersive music in spatial audio world-class workouts and meditations super fun games and more! The Services Data Science u0026 Analytics organization is passionate about developing discerning insights and AIML solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy. nnWe are currently seeking an experienced and passionate Applied ML Science Manager to lead a dynamic team whose goal is to provide innovative products at the intersection of causal inference statistics and machine learning to help drive key business decisions and optimize marketing channels via observational testing frameworks counterfactual modeling and lifetime value estimation. As a key member of our diverse organization youll have the rare and rewarding opportunity to work with datasets of unique magnitude richness and dedication to privacy that will frequently require novel approaches. Youll work alongside partners across Business Marketing Product Finance and Engineering daily to deliver material customer and business value.n

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.

Lead mentor and grow a high-performing team of Applied Scientists and Machine Learning Engineers fostering a culture of innovation and collaborationnnDrive team goals priorities and career development including recruitment and onboardingnnOversee the technical strategy design and full lifecycle of scalable robust Causal Inference and Machine Learning productsnnManage timelines resources and deliverables ensuring projects are completed on time within scope and communicated to stakeholder teamsnnCollaborate with product managers data scientists and other engineering teams to translate business requirements into technical specifications and deliver impactful practical solutions increasing internal adoption of causal inference approaches and democratizing datannStay abreast of the latest advancements in causal inference and AIML research evaluating and integrating new frameworks where appropriatennChampion best practices in software engineering MLOps code quality testing documentation and ensure compliance with data privacy and securityn

Masters degree in Statistics Economics Mathematics Machine Learning Computer Science Engineering or a related technical fieldnn3 years of experience in a leadership or management role leading Applied Scientists Machine Learning Engineers and Data Scientistsnn5 years of experience as an Applied Scientist Machine Learning or Data Scientist rolennFamiliarity 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 matchingnnWorking knowledge of Marketing Mix models and validation through Matched Market testingnnPractical expertise leveraging Customer Lifetime Value models to drive business decision-makingnnSolid understanding of AIML technologies including Generative AInnProven track record of successfully delivering complex projects from start to finishnnProficiency in programming languages such as Python R SQL Java or CnnExperience with cloud platforms Spark Docker and MLOps tools and best practicesnnExcellent communication collaboration and presentation skills with meticulous attention to detail

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