ML Data Scientist Manager, Forecasting & Supply - Apple Ads

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.\\n\\nOur 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.\\n\\nWe are looking for a Data Scientist Manager to join Apple Ads. This role sits within Core Insights, the team responsible for forecasting business performance, enabling financial planning, and providing decision-ready insights for leadership across Apple Ads.

As the MLDS Manager for Time-Series Forecasting, you will be the primary technical lead overseeing the forecasting capabilities for all advertising placements across the Apple ecosystem. Your team's models will serve as the strategic backbone for supply estimates, revenue reviews, and business context, directly impacting ad delivery in some of the world's most high-traffic digital environments.\n\nThis is a high-visibility leadership role that sits at the intersection of sophisticated Machine Learning and large-scale digital inventory. You will be responsible for building a unified, automated forecasting engine that scales across diverse surfaces-including the App Store, Apple News, and emerging inventory.\n\nBeyond model accuracy, you will champion \"Enterprise-Grade\" engineering. Your goal is to move the team toward zero-touch forecasting with full transparency, abstracting away manual workflows and infrastructure complexities. This allows your data scientists and stakeholders to move past the plumbing and focus on pushing the boundaries of what is possible in time-series analysis and LLM-powered forecasting.\n\nAs part of this team, you will:\n\n- Lead, Mentor, and Grow: Build and manage a team of data scientists, fostering a culture of technical excellence, ownership, and strong business partnership.\n- Own Forecasting Strategy: Define and drive the roadmap for forecasting models across all ad placements, ensuring high-quality supply and demand estimates.\n- Deliver Production-Grade Models: Lead the development and deployment of robust, scalable forecasting systems that support revenue planning and executive reporting.\n- Translate Insights into Decisions: Partner with Finance, Sales, and Product teams to translate model outputs into actionable business insights and strategic recommendations.\n- Advance ML Capabilities: Guide the team in applying advanced time-series and machine learning techniques, including deep learning and emerging LLM-based approaches.\n- Drive Automation and Scale: Evolve forecasting systems toward automated, low-touch solutions with strong data foundations and infrastructure.\n- Ensure Transparency and Trust: Establish frameworks for model interpretability, performance tracking, and stakeholder visibility into forecasting outputs.

7+ years of experience in data science, predictive modeling, or a related quantitative field.\n1+ years of experience in a formal management or team lead capacity, with a track record of mentoring and developing data scientists.\nStrong expertise in time-series forecasting, including both classical statistical methods (e.g., ARIMA, BSTS) and modern machine learning approaches (e.g., LSTMs, Transformers).\nProven ability to deliver models in production environments, working with large-scale, complex datasets.\nStrong communication skills, with the ability to translate technical outputs into clear business insights for cross-functional stakeholders.\nExperience working with partners in Finance, Product, or Business teams to inform decision-making.\nBachelor's degree in a quantitative field such as Computer Science, Statistics, Economics, or a related discipline.

Experience in digital advertising, marketplace dynamics, or demand/supply forecasting.\nExperience building or scaling automated data science systems and workflows.\nFamiliarity with deep learning, LLMs, or advanced ML techniques applied to forecasting problems.\nMaster's or PhD in a quantitative field.