Senior Machine Learning Engineer at SoFi

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Full Time

Start Date

Immediate

Expiry Date

29 Dec, 25

Salary

0.0

Posted On

01 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Python, SQL, AWS SageMaker, Git, Docker, CI/CD, Statistical Modeling, Supervised Learning, Unsupervised Learning, Model Risk Management, Communication Skills, Business Systems Integration, Loss Mitigation, Account Management

Industry

Financial Services

Description

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 looking for a Senior Machine Learning Engineer/Data Scientist to develop advanced machine learning models, guide measurement, strategy, and data-driven decision making to support various credit risk and operational areas for SoFi Credit Card products. The person will work closely with Credit, Risk, Product, Engineering, and Operations teams to design solutions to support acquisition, account management, and loss mitigation. These tasks involve applying state-of-the-art machine learning methodologies, deploying models into production, and developing complex business rules to solve business problems. This role is very rewarding as your work will have a direct and immediate impact on the business’ profitability. What You’ll Do Develop, implement, and continuously improve machine learning models that support various credit and operational procedures including but not limited to underwriting, account management, and loss mitigation. Implement scalable model pipelines leveraging modern ML platforms (e.g., AWS SageMaker) and best practices in version control (Git), testing, and CI/CD. Partner with Product and Engineering teams to operationalize models, including deployment, monitoring, and integration into business systems. Collaborate with the Model Risk Management team to ensure models are developed with rigor that satisfy Model Risk Management and Governance requirements. Present model performance and insights to Credit, Risk, and Business Unit leaders. Explore and leverage in-house, external, and open-source machine learning frameworks and algorithms. What You’ll Need Bachelor’s degree in Computer Science, Statistics, Mathematics, Physics, Engineering, or a quantitative field required. Master’s or Ph.D. preferred. 3+ years of relevant work experience with building, implementing, and deploying machine learning models. Excellent knowledge of machine learning and statistical modeling methods for supervised and unsupervised learning, including (but not limited to) linear regression, logistic regression, decision tree, ensemble methods, clustering, outlier detection, novelty detection. Strong programming skills in Python and SQL. Hands-on experience with ML model implementation in production environments using tools such as AWS SageMaker, Git, Docker, and CI/CD pipelines. Effective communication skills and ability to explain complex models in simple terms. Nice To Have Experience in a financial organization. Experience with model documentation and delivering effective verbal and written communication. Experience working closely with Product, Engineering, and Model Risk Management teams. 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 SoFi page! SoFi 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 SoFi is committed to an inclusive culture. As part of this commitment, SoFi 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.

Responsibilities

Develop and implement machine learning models to support credit and operational procedures. Collaborate with various teams to operationalize models and ensure compliance with risk management requirements.