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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Scientist - AppleCare WW Demand Planning - **Company:** Apple Inc. - **Location:** United States - **Experience:** Experienced - **Salary:** $184,700.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Continuous Integration, Data Structures, Data Systems, Data Warehousing, Distributed Computing Environment, Apache Hadoop, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Oracle (Applications), Raw Data, Standard Sql, Software Engineering, Snowflake, Apache Spark, Containerization, Solid Principles, Information Technology, Machine Learning Operations - **Published:** July 2, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/27814196/Machine-Learning-Scientist-Applecare-Ww-Demand-Planning-California-All-Cities-7413 ## About the Role Master's or PhD in Computer Science, Machine Learning, Statistics, Operations Research, or a related quantitative field with 3+ years of industry experience in deploying Machine Learning models OR Bachelor's degree in a quantitative field with 6+ years of industry experience in deploying Machine Learning models. Applied Machine Learning: Practical experience creating and deploying models in real-world environments, with specific expertise in Time Series forecasting, Anomaly Detection, or Optimization. Software Engineering Proficiency: Expert proficiency in Python, with a strong grasp of software design principles (Object-Oriented Design), data structures, and writing testable, maintainable code beyond just scripting. Data Systems: Expert-level SQL skills and experience working with large-scale distributed data processing frameworks (e.g., modern cloud data warehouses like Snowflake, Oracle, Spark, Hadoop, etc.). Communication: Superior ability to translate meticulous mathematical concepts into clear, actionable insights for non-technical stakeholders and leadership. Preferred Qualifications Production Engineering: Proven experience taking models from research prototypes to production systems (using CI/CD, APIs, and containerization). Creative Modeling: Ability to engineer novel features and apply advanced Time Series or ML techniques to solve complex demand challenges. Business Insight: Proficiency in translating raw data into compelling narratives that drive strategic business decisions. Mentorship: Proven track record of up-skilling teammates, bridging the gap between statistical analysis and software engineering. ## Description We are expanding our technical capabilities and seeking a Machine Learning Scientist to help us operationalize and scale our forecasting models. You will join a diverse team of data scientists and planners, bringing the specific engineering rigor needed to turn complex analyses into robust, self-improving production systems. Your work will enable the team to move faster and deploy models that directly impact resource availability for millions of customers. 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