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职位SoFi

Staff Data Scientist

SoFi

Staff Data Scientist

SoFi

CA - San Francisco

·

On-site

·

Full-time

·

2w ago

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.The Role
The Risk Data Science team is seeking a strategic and technically deep Machine Learning Engineer to lead the evolution of So Fi’s Home Loan and Home Equity risk frameworks. This role is at the center of a high-priority initiative to deliver a comprehensive, loan-level credit risk and valuation framework for our home lending portfolios.

As a key technical leader, you will apply state-of-the-art ML methodologies to solve complex problems—including default and prepayment modeling, property valuation (AVMs), and credit risk assessment—ensuring our high-value secured loan products are backed by world-class data science.

What You’ll Do

  • Lead the design and implementation of ML models for mortgage-specific use cases, including credit underwriting, debt-to-income (DTI) validation, and automated appraisal reviews.

  • Provide technical oversight and end-to-end ownership of externally developed models, ensuring they meet rigorous internal standards for quality, performance, and scalability.

  • Present model performance and portfolio insights to senior leadership, translating complex data into actionable credit and business strategies.

  • Collaborate with Model Risk Management (MRM) and governance teams to ensure all models are developed with the technical rigor required to satisfy complex regulatory and compliance standards.

  • Partner with Product and Engineering teams to operationalize models, overseeing deployment, real-time monitoring, and seamless integration into core business systems.

  • Continuously explore and leverage in-house, external, and open-source ML frameworks to build the next generation of proprietary mortgage risk tools.

What You’ll Need

  • Master’s degree in Computer Science, Statistics, Mathematics, Physics, Engineering, or a quantitative field required. Ph.D. preferred.

  • 5+ years of direct experience with building, implementing, and deploying machine learning models within Home Loans or Home Equity lending environments.

  • Expert knowledge of statistical modeling and ML methods, including linear/logistic regression, ensemble methods (XGBoost/LightGBM), clustering, and outlier detection.

  • Strong programming skills in Python and SQL.

  • Hands-on experience with ML model implementation in production environments using tools such as AWS Sage Maker, Git, Docker, and CI/CD pipelines.

  • Strong ability to distill complex technical methodologies into simple, persuasive terms for non-technical stakeholders.

Nice To Have

  • Proven track record in technical model documentation and navigating the Model Risk Management lifecycle.

  • Experience working in a cross-functional capacity across Product, Engineering, and Risk departments.

Compensation and Benefits

The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.

To view all of our comprehensive and competitive benefits, visit our Benefits at So Fi page!
So Fi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
So Fi is committed to an inclusive culture. As part of this commitment, So Fi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.

Internal Employees

If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

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关于SoFi

SoFi

SoFi

Public

SoFi Technologies, Inc. is an American financial technology company. Founded in 2011 by Stanford University students, it operates as a nationally chartered online bank and is a technology provider to other financial institutions. SoFi is the largest U.S.

1,001-5,000

员工数

San Francisco

总部位置

$8.65B

企业估值

评价

3.9

10条评价

工作生活平衡

2.8

薪酬

4.0

企业文化

4.1

职业发展

3.2

管理层

3.3

68%

推荐给朋友

优点

Flexible hours and supportive management

Excellent health benefits and competitive salary

Inclusive and diverse workplace

缺点

High workload and overwhelming work demands

Work-life balance challenges

Limited career advancement opportunities

薪资范围

16个数据点

Junior/L3

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Baseline Data Scientist

0份报告

$206,850

年薪总额

基本工资

-

股票

-

奖金

-

$175,823

$237,878

面试经验

5次面试

难度

2.0

/ 5

时长

14-28周

体验

正面 0%

中性 80%

负面 20%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Online Assessment

5

Technical Interview

6

Behavioral Interview

常见问题

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience