Senior Data Scientist, Credit Risk
Achieve
full-time
Posted on:
Location Type: Remote
Location: Remote • Nevada, Texas, Utah • 🇺🇸 United States
Visit company websiteSalary
💰 $150,000 - $185,000 per year
Job Level
Senior
Tech Stack
PythonSQLTableau
About the role
- 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 perform model and portfolio monitoring
- Perform exploratory data analysis (EDA) to identify portfolio trends, drivers of loss performance (vintage, credit bands, borrower attributes, macro factors) and provide insight into model deviations
- Maintain forecast deliverables: monthly/quarterly loss forecasts by vintage and segment, stress and scenario analyses, sensitivity testing
- Provide 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-ready 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
Requirements
- Minimum of 3 years’ hands-on experience in credit risk modeling and portfolio monitoring
- 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 related to pricing
- Experience with credit risk modeling methodologies: Scorecard models, XGBoost, time-series analysis, vintage modeling, roll-rate 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 clearly to non-technical stakeholders
- Excellent documentation skills and experience in preparing audit-ready deliverables (methodologies, assumptions, model validation support)
- Master’s degree in Economics, Statistics, Mathematics, Data Science or a related quantitative discipline (PhD preferred, but not required)
Benefits
- Hybrid and remote work opportunities
- 401 (k) with employer match
- Medical, dental, and vision with HSA and FSA options
- Competitive vacation and sick time off, as well as dedicated volunteer days
- Access to wellness support through Employee Assistance Program, Talkspace, 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 Achieve Care Fund
- A safe place to connect and a commitment to diversity and inclusion through our six employee resource groups
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
credit risk modelingportfolio monitoringSQLPythonProbabilityStatisticsXGBoosttime-series analysislogistic regressiondata visualization
Soft skills
analytical skillscritical thinkingcommunicationdocumentation skillsinsight generation
Certifications
Master’s degree in EconomicsMaster’s degree in StatisticsMaster’s degree in MathematicsMaster’s degree in Data Science