Employee Applicant Privacy Notice
Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
Social Finance LLC seeks Senior Data Scientist, Loss Forecasting in San Francisco, CA:
Job Duties: Develop advanced quantitative and machine learning models for Current Expected
Credit Loss (CECL), loss forecasting, and stress testing. Aggregate and synthesize datasets
from multiple data environments. Analyze complex datasets to understand the performance and
drivers for losses across various products. Investigate external credit data to identify trends in
the market and industry. Conduct loss sensitivity analysis. Automate models and analytical
dashboards. Monitor the models’ performance and re-calibrating the models as needed. Work
with Business Units, Operations, Product, Capital Markets, Finance, Accounting and Risk
partners to ensure correct loss expectations and trend of losses are communicated effectively
and executed appropriately. Telecommuting is an option.
Minimum Requirements: Master’s degree (or its foreign degree equivalent) in Computer
Science, Statistical Practice, (any field), or a related quantitative discipline, and four (4) years of
experience in the job offered or in any occupation in a related field.
Special Skill Requirements: Must have at least three (3) years of experience in (1) Develop
Comprehensive Capital Analysis and Review (CCAR), CECL loss forecasting models in
financial institutions using industry-standard methodologies; (2) Data Science; (3) Data
Analysis; (4) Predictive Modeling; (5) SAS or SAS Enterprise Miner; (6) Hive; (7) LaTeX; (8)
Python programming and PySpark; (9) Hadoop; and (10) Linux. Any suitable combination of
education, training and/or experience is acceptable. Telecommuting is an option.
Salary: $191,000.00 - $219,650.00 per annum.
Submit resume with references using the apply button on this posting or email to: Req.# 24-
147363 at: ATTN: HR, [email protected].
#LI-DNI
