Home Loans Loss Forecasting Analytics, Senior Data Scientist

SoFi

Quick summary

Work type
On-site
Location
Frisco, TX
Salary
$128,000–$240,000 / yr
Posted
28 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $163k
This role $184k
$96k most similar roles pay here $255k

This role pays more than 67% of similar roles. Most pay $126,800–$198,800 — the shaded band above. At the midpoint, this role pays about $184k versus about $163k for comparable roles.

Based on 240 similar postings.

Employer

About SoFi

SoFi Technologies is a fintech company offering student and personal loans, mortgages, credit cards, investing, banking, and insurance products, positioning itself as a one-stop financial services platform. Industry: Financial Technology & Personal Finance

SoFi currently has 36 open roles on FindRole.

Listed pay typically runs $153,600–$258,500 across 36 roles with salary data.

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At a glance

TL;DR · Home Loans Loss Forecasting Analytics, Senior Data Scientist

The Senior Data Scientist role at SoFi’s Secured Lending Team focuses on enhancing Home Lending risk analytics through the development of quantitative models for loss forecasting and portfolio performance monitoring across various home lending products. This individual will collaborate with cross-functional teams to build analytical frameworks, define KPIs, and create executive dashboards that provide actionable insights into credit performance metrics such as delinquency rates, cure behavior, and recovery outcomes. The ideal candidate has extensive experience in credit risk modeling, loss forecasting, and portfolio analytics, along with proficiency in Python, SQL, and data visualization tools like Tableau or Power BI. They should possess a strong understanding of mortgage credit risk drivers and be adept at statistical and machine learning methods to support SoFi’s mission in transforming financial services through robust analytical solutions.

What you'll do

  • Develop quantitative models for forecasting losses across mortgage and home equity portfolios.
  • Define and maintain KPIs for portfolio performance, including delinquency rates and cure rates.
  • Analyze borrower behavior to identify key risk drivers at different stages of credit performance.
  • Build roll-rate models and default models for secured lending portfolios.
  • Support collections analytics by evaluating resolution pathways and treatment strategies.
  • Partner with Data Engineering to improve data quality and create new data sources.

What we're looking for

  • 5+ years of experience in data science or related quantitative field
  • Strong proficiency in Python and SQL for analytical pipelines and reporting
  • Experience with credit risk modeling, loss forecasting, and CECL frameworks
  • Hands-on experience with mortgage or secured lending data products
  • Expertise in statistical and machine learning methods for financial analytics
  • Ability to communicate complex analysis to both technical and non-technical stakeholders
  • Strong understanding of mortgage credit risk drivers and portfolio performance KPIs

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