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# Data Scientist - Strategic Data Solutions

- **Company:** Apple Inc.
- **Location:** Cambridge, MA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Data Systems, Database Queries, Python (Programming Language), Machine Learning, SQL Databases, Data Processing, Scripting, Large Language Models, Apache Spark, Information Technology, Data Generation
- **Published:** September 3, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3375520745&tx=JJ9185FFQ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Masters in Statistics, Mathematics, Data Science, Machine Learning, Physics, Engineering, Computer Science or equivalent
 * Proficiency in data querying using SQL, Spark, or equivalent technologies
 * Proficiency in scripting languages for data processing and analysis (ex: Python, R, or Scala)
 * Excellent communication and multi-functional collaboration skills, ability to convey complex concepts to diverse audiences
 * At least 3 years experience working as a Data Scientist, * PhD in Statistics, Mathematics, Data Science, Machine Learning, Physics, Engineering, Computer Science or equivalent
 * Experience applying LLMs to solve technical problems such as data analysis, data automation, synthetic data generation with proven ability to optimize model performance for accuracy and efficiency
 * Excellent product intuition, keen eye for design and customer pain point awareness
 * Experience developing anomaly detection and causal inference models

## Description

As a Data Scientist, you will provide data driven insights to fight fraud. You will develop models, evaluate product launches, develop automated solutions to deliver timely alerts, find opportunities for future development by applying the bleeding edge scientific methods. You will partner with engineers, product, program and business leaders alongside other teams to bring better experiences to drive meaningful customer impact., Research and develop evaluation methods to address fraud. Solve difficult, non-routine analysis problems by applying statistical, machine learning and advanced analytical methods as needed. * Design and execute observational and experimental studies of causal inference * Work with large, complex data sets. * Develop automated solutions to deliver insights and alerts * Drive feature evaluation and product roadmap with insights


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