Achieve is looking for a Staff Data Scientist to join our team. In this hands-on role, you will work with large data sets to extract insights, maintain and enhance our credit risk models and policies, and communicate findings to stakeholders like Capital Market and Marketing teams.
What You'll Do
- Build, maintain, and enhance credit risk models for 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 to identify portfolio trends, drivers of loss performance, and provide insight into model deviations.
- Maintain forecast deliverables, including monthly/quarterly loss forecasts, 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.
- Document model methodologies, assumptions, data sources, and results in a clear, audit-ready format.
- Participate in governance and review of credit model methodology and liaise with external auditors or regulators as needed.
- Continuously identify opportunities to improve credit decisioning accuracy, data infrastructure, and modeling techniques.
What We're Looking For
- Minimum of 8 years of 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 analytics and monitoring.
- Experience with credit risk modeling methodologies like Scorecard models, XGBoost, time-series analysis, vintage modeling, or logistic regression.
- Familiarity with data visualization or dashboarding tools (e.g., Tableau, Python Widgets).
- Strong analytical skills and ability to communicate clearly to non-technical stakeholders.
- Excellent documentation skills and experience preparing audit-ready deliverables.
- Master’s degree in Economics, Statistics, Mathematics, Data Science, or a related quantitative discipline (PhD preferred).
Nice to Have
- Experience in lending (personal loans or credit cards) or a fintech lending environment.
- Experience with credit decisioning engines such as Oscilar or TakTile.
- Experience working in a CKLightbox or GCP environment.
- A passion for fintech, agile environments, and the ability to work both independently and collaboratively.
Technical Stack
- SQL
- Python
- XGBoost
- Tableau
- Python Widgets
- GCP
Benefits & Compensation
- Salary: $160,000 to $200,000 + bonus + benefits
- 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 for eligible education expenses
- Pet care discounts
- Financial support via the Achieve Care Fund
- A commitment to diversity and inclusion through employee resource groups
Work Mode
This role follows a hybrid work model and is based in Phoenix, AZ or San Francisco, CA.
Achieve is an equal opportunity employer committed to diversity, inclusion, and putting people first.
