Job Description

Role Summary



We are looking for a skilled and motivated professional to join our Risk Data Analytics and Automation team as the Sr. Credit Risk Data Analyst, based out of the Bluevine office in Bengaluru, India. The successful candidate will possess a strong analytical and technical mindset, an understanding of credit risk management and strategy implementation in code, and the ability to make data-driven decisions.


Key Responsibilities:


• Analytical and Technological Domain Development: Join our growing credit risk team to develop and manage the analytical and technological domain.
• Data-Driven Decision Making: Apply knowledge of data analytics and risk management to inform and improve decision-making processes.
• Strategy Development: Develop, implement, evaluate, and monitor strategies related to key areas of credit.
• Portfolio Risk Analysis: Conduct in-depth analyses to identify high-risk customers and recommend strategies to handle them. Support the optimization of P&L for our lending portfolio.
• Automated Decision Processes: Define and develop end-to-end automated decision processes to mitigate risk using internal decision engines and Python programming.
• Cross-Functional Collaboration: Work closely with other Bluevine teams, including Data Science, Data Engineering, R&D, Product, and other risk departments to understand different viewpoints, obtain data, make trade-off decisions, and conduct independent analysis of possible courses of action.
• Presentation: Present analysis methods and results to both technical and non-technical managers and teams within Bluevine.
• Reporting: Report functionally to the Manager of Credit Risk Analytics, based in Israel.


Required Experience and Education


• Bachelor's Degree in a quantitative field (Business, Mathematics, Economics, Finance, Statistics, Science, Engineering) from a recognized Tier 1 institution.
• Over 3 years of relevant experience in analytics with a focus on quantitative analysis.
• Strong analytical and technical skills.
• Expertise in SQL.
• Proficiency in Python.
• Experience in visualizing and presenting data insights to stakeholders using Business Intelligence (BI) tools such as Tableau or Power BI.


Preferred Experience


• Experience in financial services, such as U.S. banks, lines of credit, credit card industries, or fintech (preferred).
• Experience with credit risk products.
• Experience with process automation and code implementation.