Data Scientist

at  Apple

Austin, Texas, USA -

Start DateExpiry DateSalaryPosted OnExperienceSkillsTelecommuteSponsor Visa
Immediate12 Sep, 2024Not Specified15 Jun, 20241 year(s) or aboveRefunds,Data Structures,Color,Financial Data,Computer Science,Python,Mathematics,Data Science,Financial Institutions,Integration,Java,Texas,Real Time Data,Business Analysis,Data Warehouse,Fraud Prevention,Customer Satisfaction,Fraud,Disabilities,App StoreNoNo
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Description:

SUMMARY

Posted: Jun 10, 2024
Role Number:200554534
Imagine what you can do here. Apple is a place where extraordinary people gather to do their lives best work. Together we create products and experiences people once couldn’t have imagined, and now, can’t imagine living without. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do.

DESCRIPTION

APPLE INC has the following available in Austin, Texas. Drive dispute management processes for new and existing acquirers for Apple Media Products. Leverage dispute and fraud data analysis for fraud prevention and better dispute handling. Analyze copious amount of worldwide data for Apple Media Product (AMP) to streamline Disputes process and Payment integration. Create strategies to identify and prevent fraud. Architect, design, develop, and implement machine learning models to minimize refunds and chargebacks by aggregating and synthesizing transactional data tocounter fraud attacks. Review generated reports with AMP Financial stockholders and senior management staff to highlight the potential fraud patterns that can negatively impact customer satisfaction and Apple’s revenue. Research and analyze global customer disputes on digital product purchases originated from Apple App store. Generate statistical and trend reports using Tableau and Python to identify data anomalies in financial data due to fraudulent transactions. Establish a clear anti-fraud strategy that aligns with Apple’s overall payment and product strategy. Design automated solution to track financial fraud using Artificial Intelligence (AI) technologies. Develop high-efficiency software solution to minimize financial impact due to the fraudulent transactions. Build robust data pipelines to induct real-time data from external payment partners and financial institutions to Apple’s enterprise Data Warehouse. 40 hours/week. Apple is an Equal Employment Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities.

  • Master’s degree or foreign equivalent in Mathematics, Computer Science, Information System Management or related field and two years of experience in the job offered or related occupation. Alternatively, employer will accept a Bachelor’s degree or foreign equivalent in Mathematics, Computer Science, Information System Management or related field and five years of progressive, post-baccalaureate experience in the job offered or related occupation.
  • 1 year of experience with each of the following skills is required:
  • Business Analysis
  • Data Science
  • Expertise in Python, R, SQL, Tableau and Excel
  • Expertise in Java, Data Structures and Distributed Systems
  • Jupyter, SQL Workbench, Radar, Central Station, Quip, Github
  • SDLC & Agile

PREFERRED QUALIFICATIONS

  • N/A

ADDITIONAL REQUIREMENTS

More

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.

Responsibilities:

Please refer the Job description for details


REQUIREMENT SUMMARY

Min:1.0Max:6.0 year(s)

Information Technology/IT

IT Software - Other

Software Engineering

Graduate

Proficient

1

Austin, TX, USA