Data Scientist

Data Scientist - II, Credit Risk ML Platform

Yubi is seeking a skilled Data Scientist to join our dynamic team in Chennai. You will play a pivotal role in developing a state-of-the-art Credit Risk Machine Learning platform. This platform is designed to deliver sophisticated credit scoring models with transparent explanations, directly supporting our clients' credit monitoring and management endeavors.

Your responsibilities will include the design, development, and deployment of highly accurate, interpretable, and regulatory-compliant machine learning models for credit risk assessment. Strong Python programming skills and a solid understanding of machine learning are essential for driving innovation and delivering significant business value.

Key Responsibilities

• Develop and refine credit risk and fraud models, ensuring high accuracy and explainability to meet stringent regulatory frameworks.
• Lead the creation of a machine learning platform enabling clients to build and customize their own risk models for tailored solutions.
• Align data solutions with business objectives and technical constraints, adapting to dynamic market, regulatory, and client needs.
• Collaborate with cross-functional teams (data engineering, product, business) throughout the product lifecycle, from ideation to delivery.
• Monitor model performance and maintain risk management protocols through regular retraining, ensuring ongoing accuracy and compliance.
• Stay abreast of industry trends, regulations, and emerging technologies to continuously enhance models and the platform.
• Mentor and guide junior data scientists and engineers.

Technical Requirements

• Deep knowledge of machine learning algorithms (supervised, unsupervised, ensemble methods) and their application in risk assessment.
• Expertise in statistical analysis, including hypothesis testing, regression, probability theory, and data modeling.
• Proven experience in designing, developing, and deploying end-to-end data products.
• Proficiency in model explainability techniques (e.g., SHAP, LIME) and regulatory compliance for risk models.
• Strong proficiency in Python.
• Working knowledge of PySpark is a plus.
• Experience deploying models on cloud platforms, specifically AWS.
• Skills in developing backend microservices with FastAPI and familiarity with MLOps practices.
• Experience with Natural Language Processing (NLP) techniques is beneficial.

Domain Skills (Beneficial)

• Experience working with finance and risk teams to ensure model outputs align with business and regulatory requirements.
• Basic understanding of credit risk management processes, including credit scoring, default probability estimation, and financial regulations.
• Familiarity with finance and credit risk concepts such as loan performance, creditworthiness, and risk mitigation.

Education and Experience

• Bachelor's or advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 2 to 4 years of experience in data science and machine learning.
• Experience in the financial sector or credit risk management is advantageous.