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Applied Scientist

Apple· Services Data Science & Analytics
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Hybrid (Austin, Texas), Hybrid (Culver City, California)Full-timePosted 6mo ago

About the role

Applied Scientist role focused on causal inference, statistics, and machine learning to optimize marketing channels using observational testing frameworks, counterfactual modeling, and lifetime value estimation. You will design, develop, and deploy cutting-edge causal inference solutions, drive AI/ML initiatives, and collaborate with cross-functional teams while upholding privacy and security standards.

Responsibilities

  • Engineer end-to-end scalable and robust Causal Inference products which provide Apple with an understanding of the health of our Services’ marketing efforts.
  • Dive deep into large-scale data sources to uncover opportunities for Causal Inference automation, predictive methods, and quantitative modeling.
  • Collaborate 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 data
  • Stay abreast of the latest advancements in causal inference and AIML research, evaluating and integrating new frameworks where appropriate
  • Champion best practices in software engineering, MLOps, code quality, testing, documentation, and ensure compliance with data privacy and security
  • Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field
  • 3+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist role
  • Familiarity with a broad 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
  • Hands-on experience building Marketing Mix models and validation through Matched Market testing
  • 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

Qualifications

  • 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

Skills

Required:Causal Inference techniquesMarketing Mix modelingGenerative AIProgramming languagesCloud platforms, Spark, Docker, MLOpsCommunication & collaboration

Benefits

  • (Not specified in the provided description)
Last updated Sep 18, 2026. Interested? Apply on the company site.

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