Sr. Data Scientist (Loss Forecasting)

Achieve
San Mateo, CA

We are looking for an experienced hands-on Sr. Data Scientist / Loss Forecasting Analyst (minimum of 3 years relevant experience) who is comfortable working with large data sets coding in SQL and Python and translating forecasting results into actionable insights for business stakeholders while working closely with the capital markets team and this role you will maintain and enhance our loss forecasting methodologies/models/processes for unsecured personal loans perform vintage & segment forecasting scenario and stress testing and collaborate cross-functionally with marketing capital markets BI finance and product teams. The candidate should have an eye for automating/streamlining processes and creating workflows that are easily repeatable/replicable. You will be a key contributor to our risk management processes.

Key Responsibilities

  • Maintain and enhance loss forecasting methodologies/models/processes (e.g. for loan charge-offs delinquencies roll rates recoveries) for unsecured personal loan portfolios.
  • Extract clean and manipulate large data sets using SQL and Python; build pipelines and analytics to support forecasting and reporting.
  • 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 insight to business stakeholders on forecast outcomes assumptions model health and emerging portfolio risks.
  • Automate reporting dashboards and pipelines to streamline loss forecasting workflows 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 forecasting methodology model validation support and liaise with external auditors or regulators where needed.
  • Continuously identify opportunities to improve forecasting accuracy data infrastructure modeling techniques and integrate advanced statistical or machine-learning techniques as appropriate.

Qualifications :

Required:

  • Minimum of 3 years hands-on experience in loss forecasting (credit risk loan portfolios unsecured consumer loans or similar). For example roles in forecasting charge-offs delinquencies vintage analysis roll-rates etc.
  • Strong programming skills in Python and SQL for data analysis modeling and automation.
  • Strong skills with data visualization tools like Tableau and AI tools that materially improve productivity
  • Solid background in Probability & Statistics
  • Experience with forecasting methodologies: time-series analysis vintage modeling roll-rate curves survival analysis or logistic regression in consumer credit risk context.
  • 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).
  • Masters degree in Economics Statistics Mathematics Data Science or a related quantitative discipline (PhD preferred but not required).


Preferred:

  • Experience in unsecured consumer lending (personal loans or credit cards) or fintech lending environment.
  • Experience with forecasting for allowance/reserve processes (e.g. CECL IFRS9) or stress-testing.
  • Experience working in the GCP environment.
  • 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 $5250 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 : $150000 to $185000 salary bonus benefits.

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

Join Achieve change the future.

At Achieve were 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 youll get to be a part of their journey to a better financial future. Were proud to have over 3000 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 jobits 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 Achieves Talent Acquisition leader.

Remote Work :

No

Employment Type :

Full-time

Posted 2025-11-21

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