Jobs
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Healthcare
•401k
•Equity
•Learning
Required Skills
SQL
Python
Fraud analysis
Data analysis
Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
Apple's Strategic Data Solutions (SDS) team is looking for exceptional and experienced fraud analysts who are passionate about combating fraud, waste & abuse through close collaboration with our highly skilled Machine Learning Engineers. As a Technical Fraud Analyst, you'll have solid business acumen in e-commerce fraud mitigation, a natural curiosity to dig when you see something, and the ability to effectively communicate with their peers and leadership. You'll enjoy and have experience analyzing complex fraud scenarios, using data from both internal and external sources. You'll also be skilled at interpreting data and providing recommendations and/or driving action across your team based on your findings. In this role, you'll combine your knowledge of fraud mitigation and market landscape with data science techniques/toolsets that you will learn in order to approach fraud mitigation in a new and exciting way.
Description:
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Track operational and business metrics to align with business goals and strategies
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Perform analyses to identify fraud patterns
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Communicate findings among team and leadership as well as providing recommendations and priority among open tasks
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Decision orders in mass as demanded by current business needs
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Support discovery of new business problems and contribute to design of analytic solutions
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Ideate and recommend new, innovative ideas and adapt existing solutions to support fraud mitigation improvements
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Work closely with internal partners on critical issues, ad hoc or reoccurring analyses as required
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Ability to write executable code to solve for business needs
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Execute small scale projects
Preferred Qualifications:
BS/BA or equivalent experience in relevant field
Prior payment or post ship fraud fraud experience in an e-commerce environment
Superb communication (both written and verbal)
Demonstrable ability to develop cross functional partnerships
Tells meaningful stories and identifies solutions based on data
Demonstrates a positive can-do attitude, works efficiently in a team centric, performance-based environment or alone if tasks require it
Is comfortable dealing with ambiguity
Ability to think creatively and approach problems flexibly
Has strong organizational skills with an ability to prioritize and balance multiple activities at once
Minimum Qualifications:
Proven excellence in investigating adversarial trends, identifying behavior patterns, and responding with the appropriate actions
Demonstrates a knowledge of big data systems and programming languages such as SQL or Python.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .
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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
L2
L3
L4
L5
L6
L2 · Business Analyst L2
0 reports
$114,215
total / year
Base
$45,686
Stock
$57,108
Bonus
$11,422
$79,951
$148,480
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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