Lead / Staff Data Scientist - Credit Risk and Fraud
Aplazo
Accounting & Finance, Data Science
Bengaluru, Karnataka, India
Posted on Feb 21, 2025
Responsibilities
- Work closely with product and operation teams to implement new Credit risk and fraud risk practices using ML/DL.
- Develop highly scalable fraud risk models and tools leveraging machine learning, and deep learning models.
- 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.
- Understand the End-to-end ML pipeline ( data gathering to production ).
- 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.