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Associate Data Scientist in Shanghai at PayPal

Date Posted: 2/17/2019

Job Snapshot

  • Employee Type:
    Full-Time
  • Location:
    Shanghai
  • Job Type:
  • Experience:
    Not Specified
  • Date Posted:
    2/17/2019
  • Job ID:
    R0041337

Job Description

Fueled by a fundamental belief that having access to financial services creates opportunity, PayPal (NASDAQ: PYPL) is committed to democratizing financial services and empowering people and businesses to join and thrive in the global economy. Our open digital payments platform gives PayPal’s 267 million active account holders the confidence to connect and transact in new and powerful ways, whether they are online, on a mobile device, in an app, or in person. Through a combination of technological innovation and strategic partnerships, PayPal creates better ways to manage and move money, and offers choice and flexibility when sending payments, paying or getting paid. Available in more than 200 markets around the world, the PayPal platform, including Braintree, Venmo and Xoom enables consumers and merchants to receive money in more than 100 currencies, withdraw funds in 56 currencies and hold balances in their PayPal accounts in 25 currencies.

Primary Job Responsibilities GDS (Global Data Sciences) is a PayPal unit specializing in developing unique, best-of-breed fraud-detection solutions & cutting-edge technologies which are integrated into scalable & distributed systems that process tens of millions of events daily, evaluating fraud within hundreds of milliseconds, processing billions of dollars annually. We are seeking data scientist talent to join us. Position performs sophisticated analytics on customer activity and usage patterns and other internal and external data and other operational information from data warehouses and business processes and apply advanced behavior profiling, statistical techniques, machine learning algorithms, and expert-based methodologies to create and operationalize decisioning logic and solutions.

Job Responsibilities

  • Perform statistical data analysis and understanding, ensure data quality, and develop tracking and reporting systems to determine the effectiveness of models, rules, and other risk initiatives and programs.
  • Mine and analyze massive amount of unique internal and external data to gain deep business knowledge and insight on customer activity and usage behaviors and their relationships with fraud and credit risks and other types of behaviors.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              
  • Design, develop, implement, execute, and monitor scoring models, expert rules and other types of decision analytics to detect fraud risk and credit risks by leveraging expert-based methodologies, advanced statistical techniques, and machine learning algorithms, such as regressions, neural networks, decision trees, and etc.
  • Perform data-driven as well as expert-driven decision optimization to optimize risk decision strategies and rules for taking appropriate actions at each customer touch point and at each stage of customer lifecycle to achieve optimal balance between loss reduction, customer experience, revenue enablement, and cost of losses.
  • Research and develop new methodologies and techniques to improve the overall effectiveness of decision analytics and decision management
  • Develop and implement analytic tools and automation processes to improve the overall efficiency of delivery of decision management solutions

Requirements

  • BS/BA degree in related field required or equivalent professional work related experience.
  • 2+ years related professional experience or Master’s degree and 1+ year.
  • High proficiency in fundamental technical skills(Programming language like Python/R/Java; database language like SQL; strong UNIX background; working knowledge of Hadoop, Map-Reduce, Hive, Pig)

We're a purpose-driven company whose beliefs are the foundation for how we conduct business every day. We hold ourselves to our One Team Behaviors which demand that we hold the highest ethical standards, to empower an open and diverse workplace, and strive to treat everyone who is touched by our business with dignity and respect. Our employees challenge the status quo, ask questions, and find solutions. We want to break down barriers to financial empowerment. Join us as we change the way the world defines financial freedom.

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities.

R0041337

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