Applied Scientist

Apple Inc

Quick summary

Work type: On-site
Location: Austin, TX
Posted: 42 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $179k

$114k most similar roles pay here $243k

This listing doesn't post a salary. Most similar roles pay $126,800–$230,306.

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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Applied Scientist

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The Applied Scientist role within the Services Data Science & Analytics team at a leading tech company requires an experienced professional to develop innovative causal inference solutions for optimizing marketing channels. This senior-level position involves designing, developing, and deploying cutting-edge Causal Inference products to enhance product effectiveness and customer engagement. Daily responsibilities include collaborating with cross-functional teams to translate business requirements into technical specifications, ensuring the delivery of scalable and impactful models that adhere to data privacy standards. The ideal candidate possesses a Master’s degree in Statistics, Economics, Mathematics, or related fields, along with extensive experience in causal inference techniques and proficiency in Python, R, SQL, Java, or C++. Familiarity with cloud platforms like Spark and MLOps tools is essential for working on large-scale datasets that demand novel approaches to maintain customer privacy.

Skills

Python R SQL Java C++ AWS Spark Docker MLOps CI/CD Generative AI Causal Inference Marketing Mix Models Quasi-experimental Techniques Diff-in-diff Synthetic Control Method Panel Analysis Regression Discontinuity Design Interrupted Time Series Propensity Score Matching

What you'll do

Develop and deploy scalable Causal Inference solutions for marketing optimization.
Analyze large datasets to automate causal inference methods and predictive modeling.
Translate business requirements into technical specifications for data-driven projects.
Evaluate and integrate new frameworks in causal inference and AIML research.
Champion software engineering best practices, ensuring compliance with privacy standards.

What we're looking for

Master’s degree in a relevant technical field such as Statistics, Economics, or Computer Science.
3+ years of experience in Applied Scientist, Machine Learning, or Data Scientist roles.
Expertise in various quasi-experimental Causal Inference techniques and Marketing Mix models.
Strong understanding of AIML technologies including Generative AI and proficiency in Python/R/SQL.
Successful track record delivering complex projects from conception to completion.
Experience with cloud platforms, Spark, Docker, and MLOps tools for scalable solutions.

Applied Scientist

Opendoor

Miami, FL 31 days ago $156,800–$335,000

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