Data Scientist in London at PayPal

Date Posted: 1/8/2020

Job Snapshot

  • Employee Type:
    Full-Time
  • Location:
    London
  • Job Type:
  • Experience:
    Not Specified
  • Date Posted:
    1/8/2020
  • Job ID:
    R0049497

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 286 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.

Simility’s Data Scientists are comprehensive modeling experts who collaborate within a team of industry experts and data scientist, to ensure that their customers are successful in their deployments in catching fraud and malicious activities. They continually improve and apply their technical knowledge and skills across the product suite at every level of the customer engagement. The successful Data Scientist will exhibit and build upon the deep expertise to ensure that they can not only have a successful machine learning driven solution but can also explain those to business teams leading to a happy customer. Customer related work being one part of the DS role within Simility, DS team members spend significant amount of their time solving problems that affect many parts of the organization, including domain-driven research, ML-focused product innovations, automation and process improvements to continuously contribute to the success of Simility.

Primary Responsibilities: 

  • Work with internal and external clients to creatively leverage new and existing data sources to increase the effectiveness and efficiency of our existing suites of machine learning models. 
  • Work on top of a state-of-the-art technology stack and together with a dedicated data science engineering team to design ml-driven solutions that operate at scale and in real-time.
  • Make business recommendations to the executive and cross-functional teams with effective presentations of findings at multiple levels of stakeholders.
  • Lead and participate in special initiatives: innovate and implement large-scale quality improvements to processes and/or systems by conducting data analysis and making recommendations, troubleshooting technical issues, and refining processes
  • Help understand the main customer issues around fraud and compliance 
  • Understand the nature of the data that is going to be provided and work with the customer to create and finalize a data schema that meets their needs 
  • Perform in-depth analysis on data sets to detect anomalies and to understand the key parameters that may be indicative of fraud
  • Analyze and transform data using the Simility platform to identify fraud patterns and optimize the system to flag these patterns 
  • Communicate insights and findings back to the team to contribute to overall teams’ success
  • Train the customer on machine learning techniques, data science and how to use the ml-driven Simility platform
  • Improving the product with innovative ideas driven by customer feedback; working with product development team to incorporate those feedback into the platform

Qualifications and Experience:

  • BA/BS or MA/MSc Degree in Computer Science, Engineering, Mathematics, Statistics, Data Mining or related field or equivalent practical experience. 
  • A minimum of 2 years of experience in Data Science, Data Analysis, Research, Risk and Fraud Investigation. 
  • Programming experience, preferred in Python, R, or any other statistical scripting language plus relevant statistical and machine learning libraries and packages

Preferred Experience: 

  • Risk, fraud detection experience is highly preferred but not required. 
  • PhD in a STEM field or master's degree plus 2-3 years of experience in Data Science or Machine Learning, Statistics, Optimization, or related field, with experience building production-ready ML models and systems; 
  • Industry experience in one of the following areas: online payment, fintech, eCommerce, online advertising and publishing, 
  • Ideally working experience in developing machine learning models for fraud, credit or risk detection at scale from inception to business impact. 
  • Previous experience working with Spark, SQL/Hive, JavaScript and UNIX
  • Hands-on experience in building reliable and scalable training and real-time inference pipelines; knowledge of deployment, monitoring and managing machine learning models
  • Deep understanding of and experience of modern machine learning techniques such as classification, clustering, recommendation systems, graph-analysis and other shallow learning techniques, data analytics, and statistical models.
  • Ability to clearly articulate and confidently present findings and technical details to executives and a non-technical audience
  • Deep learning experience preferred but not a requirement

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. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

R0049497