Senior Staff Data Scientist, Loss Forecasting

SoFi Technologies
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Job Description

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 fintech company 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 and Operations Data Science team is looking for a Data Scientist to develop advanced machine learning models, guide measurement, strategy, and data-driven decision making to support various credit risk and operational areas at SoFi. The Data Scientist will work closely with Credit, Risk, Product, Engineering, and Operations teams to design solutions to support credit underwriting, enhance loan processing, prevent login fraud and account take over, and support loss mitigation, etc. These tasks involve developing complex business rules to researching and applying state of the art machine learning modeling methodologies to solve complex 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 and strategies that support various credit and operational procedures including but not limited to underwriting, loan processing, loss mitigation, and fraud/account takeover, etc
  • Proactively identify opportunities to apply advanced machine learning approaches (e.g., NLP, Image Recognition, Graph Mining, etc) to solve complex business problems
  • Explore and leverage in-house, external, and other open-source machine learning software/algorithms
  • Collaborate with Model Risk Management team to demonstrate models are developed with high level rigor that satisfy Model Risk Management and Governance requirements
  • Work closely with the Product and Engineering teams for model deployment
  • Perform ongoing monitoring of the models through the construction of dashboards and KPI tracking
  • Present model performance and insights to Credit, Risk, and Business Unit leaders

What You’ll Need

  • Bachelor’s degree in Computer Science, Statistics, Mathematics, Physics, Engineering, or quantitative field required. Master’s or Ph.D. degree preferred.
  • 3+ years of relevant work experience with building and implementing machine learning models
  • Excellent knowledge of machine learning and statistical modeling methods for supervised and unsupervised learning. These methods include (but not limited to) linear regression, logistic regression, decision tree, ensemble methods, clustering, outlier detection, novelty detection, deep learning and its various applications. Continuously follow the advancement of machine learning and artificial intelligence to update your knowledge and skills in order to solve business problems with the most efficient methodologies
  • Strong programming skills in Python
  • Strong knowledge of databases and related languages/tools such as SQL, NoSQL, Hive, etc.
  • 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 in working closely with Product, Engineering, and Model Risk Management teamsCompensation and BenefitsThe 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!Pay range: $118,400.00 - $222,000.00Payment frequency: AnnualThis role is also eligible for a bonus, long term incentives and competitive benefits. More information about our employee benefits can be found in the link above.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 RightsSoFi is committed to embracing diversity. 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 EmployeesIf you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Company Info.

SoFi Technologies

SoFi Technologies, Inc. is an American online personal finance company and online bank. Based in San Francisco, SoFi provides financial products including student and auto loan refinancing, mortgages, personal loans, credit card, investing, and banking through both mobile app and desktop interfaces.

  • Industry
    Financial services,Banking,FinTech
  • No. of Employees
    2,500
  • Location
    San Francisco, CA, USA
  • Website
  • Jobs Posted

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