Data Scientist, Strategic Data Solutions

Apple Inc

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Quick summary

Work type: On-site
Location: Austin, TX
Posted: 34 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $162k

$97k most similar roles pay here $225k

This listing doesn't post a salary. Most similar roles pay $126,800–$198,000.

Based on 240 similar postings.

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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 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Data Scientist, Strategic Data Solutions

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As a Data Scientist - Strategic Data Solutions, you will join the Apple Store Online team to provide data-driven insights specifically aimed at fighting fraud. You will be responsible for developing scalable data solutions, designing and executing observational and experimental studies of causal inference, and creating automated systems to deliver timely alerts. Your daily work involves solving non-routine analysis problems using statistical methods, machine learning, and advanced analytics while influencing upstream data model design and KPI definitions. To succeed in this role, you must be proficient in SQL, Spark, or equivalent querying tools, along with scripting languages like Python, R, or Scala. You will also leverage LLMs for data automation and synthetic data generation to improve customer experience and drive the product roadmap through sophisticated analysis of large, complex datasets.

What does a Data Scientist earn?

Median $162025 from 276 postings across 61 companies.

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Skills

SQL Spark Python R Scala Machine Learning LLMs Causal Inference Anomaly Detection Data Automation Synthetic Data Generation

What you'll do

Develop and implement machine learning models and advanced analytical methods to detect and fight fraud.
Design and execute observational and experimental studies using causal inference techniques.
Build automated solutions to deliver timely alerts and insights from large, complex datasets.
Create scalable data solutions to drive reporting, analysis, and key performance indicator definitions.
Measure the impact of product features and initiatives to improve the customer experience.
Influence upstream data model design and inform the product roadmap with data-driven insights.
Communicate technical findings and results to both technical and non-technical senior leadership.

What we're looking for

Master's degree in Statistics, Mathematics, Data Science, Machine Learning, Physics, Engineering, Computer Science, or a related field.
PhD in Statistics, Mathematics, Data Science, Machine Learning, Physics, Engineering, or Computer Science is preferred.
At least 3 years of experience working as a Data Scientist.
Proficiency in data querying using SQL, Spark, or equivalent technologies.
Proficiency in scripting languages for data processing and analysis such as Python, R, or Scala.
Experience developing anomaly detection and causal inference models.
Experience applying LLMs to solve technical problems like data analysis, automation, and synthetic data generation.
Excellent communication skills to convey complex concepts to both technical and non-technical audiences.