Achieve is hiring a Sr. Data Scientist (Credit Risk) to build and enhance models that manage risk for our digital personal finance platform. You will be responsible for the full lifecycle of our credit risk models, from development and maintenance to monitoring and governance, providing key insights that drive business decisions.

What You'll Do

Build, maintain, and enhance credit risk models for our lending portfolios.
Extract, clean, and manipulate large data sets using SQL and Python; build pipelines and analytics for model and portfolio monitoring.
Perform exploratory data analysis (EDA) to identify portfolio trends, drivers of loss performance, and provide insight into model deviations.
Maintain monthly and quarterly loss forecasts by vintage and segment, including stress and scenario analyses and 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 a 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.
Continuously identify opportunities to improve credit decisioning accuracy, data infrastructure, and modeling techniques.

What We're Looking For

A Master’s degree in Economics, Statistics, Mathematics, Data Science, or a related quantitative discipline.
Minimum of 3 years of hands-on experience in credit risk modeling and portfolio monitoring (e.g., model and performance monitoring, tracking charge-offs, delinquencies, vintage analysis, roll-rates).
Strong programming skills in Python and 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).

Nice to Have

Experience in lending (personal loans or credit cards) or a fintech lending environment.
Experience with credit risk modeling (development & monitoring).
Experience working with credit decisioning engines such as Oscilar or TakTile.
Experience working in a 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.

Technical Stack

SQL
Python
XGBoost
Tableau
GCP

Benefits & Compensation

Salary range: $150,000 to $185,000
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, plus dedicated volunteer days
Access to wellness support through Employee Assistance Program, Talkspace, and fitness discounts
Up to $5,250 paid back on eligible education expenses
Pet care discounts
Financial support in times of hardship with Achieve Care Fund
Commitment to diversity and inclusion through six employee resource groups