Applied Scientist

Apple Inc

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Quick summary

Work type: On-site
Location: Culver City, CA
Salary: $175,000–$308,500 / yr
Posted: 179 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $202k

This role $242k

$125k $328k

below market most similar roles pay here above market

This role pays more than 75% of similar roles. Most pay $162,000–$241,906 — the blue band above. At the midpoint, this role pays about $242k versus about $202k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · Applied Scientist

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The Applied Scientist joins the Services Data Science & Analytics organization to develop AIML solutions that improve services while maintaining customer privacy. This role involves designing, developing, and deploying scalable Causal Inference products to optimize marketing channels through observational testing frameworks, counterfactual modeling, and lifetime value estimation. You will engineer end-to-end products to understand marketing effectiveness, dive into large-scale data sources for predictive modeling, and translate business requirements into technical specifications. Key technologies and skills include Python, R, SQL, Java, or C++, Spark, Docker, and MLOps tools. You must apply quasi-experimental techniques like diff-in-diff, synthetic control, and propensity score matching. The work focuses on solving complex customer acquisition and engagement challenges by leveraging Generative AI and advanced statistics to provide granular insights into marketing health.

What does a Applied Scientist earn?

Median $208800 from 61 postings across 10 companies.

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Skills

Causal Inference Machine Learning Generative AI Python R SQL Java C++ MLOps Spark Docker Statistics Counterfactual Modeling Diff-in-diff Synthetic Control Method Propensity Score Matching

What you'll do

Engineer end-to-end scalable and robust Causal Inference products to measure marketing effectiveness.
Analyze large-scale data sources to identify opportunities for automation, predictive methods, and quantitative modeling.
Translate business requirements into technical specifications to deliver practical AIML solutions.
Define the technical vision, strategy, and execution roadmap for AIML initiatives.
Integrate the latest research and frameworks in causal inference and AIML into existing products.
Implement best practices in software engineering, MLOps, code quality, and data privacy compliance.
Develop models for customer acquisition, engagement, and lifetime value estimation.

What we're looking for

Master’s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field.
PhD in a related field (preferred).
3+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist.
Familiarity with quasi-experimental Causal Inference techniques like diff-in-diff, synthetic control, 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.
Proficiency in programming languages such as Python, R, SQL, Java, or C++.
Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices.