Credit Risk Analyst

• Data is central to decision-making at Fi and our analysts play a major role in driving strategic decisions
• Teams across functions from product and finance to tech and marketing collaborate with our analysts for insights to make informed decisions
• Analysts at Fi work with data to craft compelling narratives towards decisions that take the product to the next level
• Were all about the pursuit of making more intelligent and faster decisions at Fi through analytics
• We take this endeavor very seriously while having fun creating value for ourselves and the organization

Roles and Responsibilities:

• Conduct thorough credit assessments on loan applications, evaluating factors such as credit history, financial statements, and collateral.
• Utilize statistical models and risk assessment tools to analyze creditworthiness and determine appropriate lending terms.
• Monitor and manage credit exposure by identifying potential risks and implementing risk mitigation strategies.
• Collaborate with internal teams, including underwriting and collections, to optimize credit processes and improve portfolio performance.
• Stay updated on industry regulations and market trends to ensure compliance with relevant guidelines and best practices.
• Prepare detailed reports and presentations summarizing credit risk metrics and performance indicators for senior management.
• Participate in cross-functional projects aimed at enhancing credit risk management practices and driving business growth.

Some ideal things to have:

• A passion for analytics, a love of what it is - tough, intriguing, never dull, always intellectually challenging and constantly demanding that you expand your skill set
• Strong in first principle-thinking and applying analytics to real-life business problems
• Can maintain a clear style of communication and is able to coordinate with people from different teams and backgrounds. Effective storyteller with the ability to connect the dots and explain the crux of a situation to the stakeholders
• Ability to self-manage priorities and deliverables while working in a fast-paced, startup environment
• A solid understanding of data structures and expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods as well as scenario-based sensitivity analyses
• Experience with one or more data programming languages (Python, R, SQL) and one or more visualization tool (Tableau, PowerBI, Qlikview, D3.Js )
• Conduct every analysis with speed, quality and reliability