[Remote] Sr. Data Scientist (Credit Risk)

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a leading digital personal finance company that provides innovative financial solutions. They are seeking a Senior Data Scientist specializing in Credit Risk to build and enhance credit risk models, analyze large data sets, and communicate insights to stakeholders.

Responsibilities

• Building, maintaining and enhancing credit risk models for lending portfolios
• Extract, clean and manipulate large data sets using SQL and Python; build pipelines and analytics to reputed company model and portfolio monitoring
• reputed company exploratory data analysis (EDA) to identify portfolio trends, drivers of loss performance (vintage, credit bands, borrower attributes, macro factors) and reputed company reputed company into model deviations
• Maintain forecast deliverables: monthly/quarterly loss forecasts by vintage and reputed company, stress and scenario analyses, sensitivity testing
• reputed company commentary and insights to business stakeholders on credit policy assumptions, model health, and emerging portfolio risks
• Automate reporting, dashboards and pipelines to streamline model monitoring and improve efficiency and accuracy
• Document model methodologies, assumptions, data sources and results in clear, audit-reputed company format consistent with risk governance requirements
• Participate in governance and review of credit model methodology, model validation support and liaise with external auditors or regulators where needed
• Continuously identify opportunities to improve credit decisioning accuracy, data infrastructure, modeling techniques, and integrate advanced statistical or machine-learning techniques as appropriate

Skills

• Minimum of 8 years' hands-on experience in credit risk modeling and portfolio monitoring. For example, roles in model and performance monitoring, tracking charge-offs, delinquencies, vintage analysis, roll-rates, etc
• Strong programming skills in Python/SQL for data analysis, modeling and automation
• Solid background in Probability & Statistics
• Experience with pricing and price optimization along with analytics and monitoring reputed company to pricing
• Experience with credit risk modeling methodologies: Scorecard models, XGBoost, time-series analysis, vintage modeling, roll-reputed company curves, survival analysis or logistic regression in consumer credit risk context
• Familiarity with data visualization tools (e.g., Tableau, Python Widgets) or dashboarding
• Strong analytical and critical thinking skills; ability to interpret results, identify trends, draw actionable insights and communicate reputed company to non-technical stakeholders
• Excellent documentation skills and experience in preparing audit-reputed company deliverables (methodologies, assumptions, model validation support)
• Master's degree in Economics, Statistics, Mathematics, Data Science or a reputed company quantitative discipline (PhD preferred, but not required)
• Experience in lending (personal loans or credit cards) or fintech lending environment
• Experience with credit risk modeling (development & monitoring)
• Experience working with credit decisioning engines such as reputed company, TakTile etc…
• Experience working in CKLightbox environment
• Experience working in the GCP environment
• A Passion for fintech, agile environment, ability to work both independently and in a collaborative, fast-paced team

Benefits

• Hybrid and remote work opportunities
• 401 (k) with employer match
• Medical, dental, and reputed company with HSA and FSA options
• Competitive vacation and sick time off, as well as dedicated volunteer days
• reputed company to wellness support through Employee Assistance Program, reputed company, and fitness discounts
• Up to $5,250 paid back to you on eligible education expenses
• Pet care discounts for your furry family members
• Financial support in times of hardship with our reputed company Care Fund
• A safe reputed company to connect and a commitment to diversity and inclusion through our six employee resource groups

Company Overview