Role:                      Data Scientist

Company:            PayU Payments Pvt Ltd

Location:            Gurgaon

 

About Company:

PayU, the fintech-arm of Naspers, is a leading financial services provider in global growth markets. We use our expertise and heritage in cross border and local payments to extend the services we offer to merchants and consumers. Our local operations span 18 growth markets across Asia, Central and Eastern Europe, Latin America, the Middle East and Africa. PayU India forays into two business verticals - payment offerings under PayU Payments Services Ltd. and alternate lending under PayU Finance. Headquartered in Sohna Road, Gurgaon, the company has a presence in Mumbai, Pune and Bangalore and has a total strength of 600+ employees. Mr. Anirban Mukherjee is the CEO for PayU India working with the global CEO Laurent Le Moal.

Under the aegis of PayU Payments Services Ltd., PayU provides payment gateway solutions to online businesses through its cutting-edge and award-winning technology. In India, PayU covers nearly 60% of the airline business and 90% of the entire e-commerce business and processes over INR 95,000 crores worth of digital payments annually. The company offers more than 70 local payment methods and serves more than 350,000 merchants including leading ecommerce businesses in India. The company also empowers SMBs, enabling them to accept mobile and online payments with minimum development effort. PayU India has processed more than 1 Billion transactions, the date for which is being used for offering Credit services.

With credit being the key business priority, PayU has also developed LazyPay, an alternate lending platform to offer credit solutions such as Small Ticket Credit (Buy Now, Pay Later), App based personal loans and Point of Sale Credit (Merchant EMI). Since its launch in 2017, LazyPay has gained significant traction and has disbursed 20mn+ loans to a customer base of a million user.

This role is with the Global analytics function for Credit and Payments, with specific focus on improving our credit offerings in India, Colombia and Poland.

What you will be doing:

As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for carrying out analytical initiatives which will be as follows: -

  • Dive into the data and identify patterns
  • Development of end-to-end Credit models and credit policy for our existing credit products
  • Leverage alternate data to develop best-in-class underwriting models
  • Working on Big Data to develop risk analytical solutions
  • Development of Fraud models and fraud rule engine
  • Collaborate with various stakeholders (e.g. tech, product) to understand and design best solutions which can be implemented
  • Working on cutting-edge techniques e.g. machine learning and deep learning models

Example of projects done in past:

  • Lazypay Credit Risk model using CatBoost modelling technique ; end-to-end pipeline for feature engineering and model deployment in production using Python
  • Fraud model development, deployment and rules for EMEA region

 

Basic Requirements:

  • 1-3 years of work experience as a Data scientist (in Credit domain)
  • 2016 or 2017 batch from a premium college (e.g B.Tech. from IITs, NITs, Economics from DSE/ISI etc)
  • Strong problem solving and understand and execute complex analysis
  • Experience in at least one of the languages - R/Python/SAS and SQL
  • Experience in in Credit industry (Fintech/bank)
  • Familiarity with the best practices of Data Science

 

Add-on Skills : 

  • Experience in working with big data
  • Solid coding practices
  • Passion for building new tools/algorithms
  • Experience in developing Machine Learning models

 

Behavioural Skills:  

  • Team Player
  • Perseverance
  • Knowledge sharing skills
  • Energetic & Positive attitude
  • Go getter instinct

 

So what do we offer?  

  • Opportunity to work on exceptional projects using cutting edge technology in big data environment
  • A Competitive salary, including benefits
  • Modern offices with individual working spaces
  • Awesome teams that love finding ways of making things better, faster, stronger
  • Interesting growth prospects

 

 

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