Senior Staff Data Scientist

Job Description

We are looking for an experienced, hands-on Credit Risk, Sr. Staff Data Scientist who is comfortable working with large data sets, coding in SQL and Python and gaining insights from the data and translating the results into actionable insights for business stakeholders. In this role, you will maintain and enhance our credit risk models/policies to monitor the portfolio and gain insights. You will also build and monitor credit risk models with an eye on loss forecasting and communicate the results to different teams such as Capital Market and Marketing. The candidate should have a passion for streamlining processes and building tools which can monitor models/portfolio effectively. You will be a key contributor to our risk management processes.

Key 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 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.

Qualifications

Required:

• 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 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).

 Preferred:

• 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 Oscilar, 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.

Additional Information

Achieve well-being with:

• 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

Note: We will be unable to facilitate H1-B Visa transfer or sponsorship, along with STEM-OPT Visa.

Work from home/hybrid:

We are proudly offering hybrid options in the Phoenix, AZ and San Francisco, CA metro market. We are offering 100% remote work in other approved locations.

Salary Range: $160,000 to $200,000 salary + bonus + benefits.

This information represents the expected salary range for this role. Should we decide to make an offer for employment, we'll consider your location, experience, and other job-related factors.

Join Achieve, change the future.

At Achieve, we’re changing millions of lives.
From the single parent trying to catch up on bills to the entrepreneur needing a loan for the next phase of growth, you’ll get to be a part of their journey to a better financial future. We’re proud to have over 3,000 employees in mostly hybrid and 100% remote roles across the United States with hubs in Arizona, California, and Texas. We are strategically growing our teams with more remote, work-from-home opportunities every day to better serve our members. A career at Achieve is more than a job—it’s a place where you can make a true impact, have a sense of belonging, establish a fulfilling career, and put your well-being first.

Attention Agencies & Search Firms: We do not accept unsolicited candidate resumes or profiles. Please do not reach out to anyone within Achieve to market your services or candidates. All inquiries should be directed to Talent Acquisition only. We reserve the right to hire any candidates sent unsolicited and will not pay any fees without a contract signed by Achieve’s Talent Acquisition leader.