Fraud Model Developer at SoFi

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Full Time

Start Date

Immediate

Expiry Date

18 Dec, 25

Salary

0.0

Posted On

19 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Python, SQL, Tableau, Statistical Methodologies, Fraud Reduction Methodologies, Loss Forecasting, Decision Trees, Gradient Boosting, Random Forests, Neural Networks, Clustering Analysis, Problem Solving, Data Analytics, Empirical Measurements

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: We are looking for a Data Scientist and/or Machine Learning model developer to join our Fraud Model Development Team. This team member’s responsibilities include model development and performance monitoring supporting data-driven decision-making in partnership with our Fraud and Risk management teams. The Data Scientist will play a key role in developing Fraud models to reduce loss, minimize false positives and ultimately help SoFi protect our members. These models will apply to all SoFi products and services including Personal Loans, Student Loans, Credit Cards and Crypto. The Staff Data Scientist will contribute to the performance analysis of SoFi products using empirical measurements, develop quantitative and machine learning models to minimize Fraud losses and provide insights on the drivers for losses. She/He will also collaborate with the Business Units, Finance, Accounting, Operations and Fraud Risk groups. This position requires knowledge of data analytics and modeling using Python and machine learning/analytical packages as well as strong problem solving skills. The ideal candidate should have hands-on knowledge on common Fraud reduction methodologies and excellent knowledge of data science, statistical methodologies and machine learning models (e.g. linear regression, logistic regression, decision trees, gradient boosting, random forests, neural network, clustering analysis etc.). By joining SoFi, you'll become part of a forward-thinking company that is transforming financial services for the better. We offer the excitement of a rapidly growing startup with the stability of an industry leading leadership team. What you’ll do: The Data Scientist will help SoFi develop better data driven modeling solutions by: Developing quantitative/machine learning models to reduce Fraud losses, and OpEx related to supporting Fraud complaints and disputes Aggregating and synthesizing datasets from multiple data environments Analyzing complex datasets to understand the performance and drivers for losses across various products Investigating external risk data to identify trends in the market and industry Conducting loss sensitivity analysis Automating models and analytical dashboards Monitoring the models’ performance and re-calibrating the models as needed Working 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 What you’ll need: 5+ years of loss forecasting experience and/or a Master’s or PhD degree in Statistics, Mathematics, Economics, Engineering, Computer Science, or a quantitative field Proficient in Python, SQL & Tableau Experienced in model development and data analysis with deep knowledge of data science, statistical methodologies and machine learning models, e.g. linear regression, logistic regression, decision trees, gradient boosting, random forests, neural network, clustering analysis etc. Hands-on knowledge on common loss forecasting methodologies Someone who is highly motivated and drives change, is eager to learn and able to work collaboratively in a complex and fluid environment Nice to have: Familiarity working with graph databases Experience with developing and productionizing models in the AWS environment a plus 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

The Data Scientist will develop quantitative and machine learning models to reduce fraud losses and analyze complex datasets to understand performance and drivers for losses. They will also collaborate with various business units to ensure effective communication of loss expectations and trends.