Applied Scientist

Apple • Austin, TX

5d

About The Position

Apple’s Services Data Science & Analytics organization develops insights and AI/ML solutions to improve services and accelerate growth while maintaining a strong dedication to customer privacy. The Applied Scientist will develop innovative products at the intersection of causal inference, statistics, and machine learning, helping optimize marketing channels through observational testing frameworks, counterfactual modeling, and lifetime value estimation. The role works with large, rich datasets and collaborates daily with partners in Business, Marketing, Product, Finance, and Engineering.

The Applied Scientist will design, develop, and deploy causal inference solutions that affect products and provide a detailed understanding of marketing effectiveness. The role also helps define the technical vision, strategy, and execution roadmap for AI/ML initiatives, delivering high-quality, scalable models to address customer acquisition and engagement challenges. The scientist will contribute to a culture of innovation, continuous learning, and collaborative problem-solving.

Requirements

• Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field.
• At least 3 years of experience in an Applied Scientist, Machine Learning, or Data Scientist role.
• Familiarity with a broad range of quasi-experimental causal inference techniques, such as difference-in-differences, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, and propensity score matching.
• Hands-on experience building Marketing Mix models and validating them through Matched Market testing.
• Solid understanding of AI/ML technologies, including Generative AI.
• 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 a related field.
• Hands-on experience leveraging Generative AI to improve productivity and generate new insights.
• Curious business attitude and ability to condense complex concepts and models into clear, concise takeaways that drive action.

Responsibilities

• Design, develop, and deploy causal inference solutions that directly impact products and measure marketing effectiveness.
• Develop solutions to optimize marketing channels using observational testing frameworks, counterfactual modeling, and lifetime value estimation.
• Help define the technical vision, strategy, and execution roadmap for AI/ML initiatives.
• Deliver high-quality, scalable, and impactful models addressing customer acquisition and engagement challenges.
• Collaborate with partners across Business, Marketing, Product, Finance, and Engineering.
• Foster innovation, continuous learning, and collaborative problem-solving.

What This Job Offers

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