Sr. Data Scientist - Credit and Fraud

Company name confidential

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2-6 Years

INR 13.1 - 16.5 LPA

ITES/BPO/Call Center

Job Description

HIRING FOR INFOSYS

Responsibilities:

Work closely with product and operation teams to implement new fraud prevention practices using ML/DL.
Develop highly scalable fraud risk models and tools leveraging machine learning, deep learning, and rules-based models.
Work closely on due diligence and integration of 3rd party fraud prevention vendors.
Build state-of-the-art fraud risk models using alternative data such as device data, network data, etc.
Build various credit risk models (underwriting model, behavior risk model, propensity model, etc. ).
Build capabilities to automatically manage credit lines for users based on optimization techniques.
Own the Data Science model end-to-end, from data collection to model building, to monitoring the model in production.
Build Machine Learning and Deep Learning models in the customer lifecycle which include Personalization, Recommendation, Rewards, Referrals, Transaction Categorization, and Customer Science-related models.
Understands the End to End ML pipeline.

Requirements:

Bachelor's or Master's degree in Computer Science, Information management, Statistics, or a related field, with 2 to 6 years of relevant work experience.
Experience in risk specifically in credit or fraud risk at alternative lending, buy-now-pay-later, payment, credit card, or top-tier consultancy companies.
Python programming skill is a must. Strong coding capabilities in ML and Deep learning.
Experience in statistical modeling, machine learning, data mining, unstructured data analytics, and natural language processing.
Sound understanding of - Bayesian Modeling, Classification Models, Cluster Analysis, Neural Networks, Nonparametric Methods, Multivariate Statistics, etc.
Familiarity with basic ML Engineering concepts, and understanding of OOP programming concepts.
Strong in data analysis and data wrangling. Experience with common libraries and frameworks in data science.
Familiarity with database queries and data analysis processes (SQL, Python).
Outstanding leadership, influencing, communication, interpersonal, and teamwork skills.
Detail-oriented, with the ability to work both independently and collaboratively.
Any prior research publication is a plus point.