Sr Staff Data Scientist - Machine Learning
Sr Staff Data Scientist - Machine Learning
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Job Description
The role:
The Risk Data Science team is looking for a Sr Staff Data Scientist to develop advanced machine learning models guide measurement strategy and datadriven decision making to support various credit risk areas at SoFi. The Sr Staff Data Scientist will work closely with Credit Risk Product Engineering teams to design solutions for loss mitigation and loss forecasting. These tasks involve 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.
By joining SoFi youll become part of a forwardthinking 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 youll do:
The Senior Staff Data Scientist will help SoFi develop better data driven model solutions by:
- Proactively identify opportunities and collaborate cross functionally to develop implement and continuously improve machine learning models and strategies that support various credit and operational procedures for loss mitigation and loss forecasting
- Proactively identify opportunities to apply AI and advanced machine learning approaches to solve complex business problems
- Evaluate alternative data sources and external vendor solutions by defining and driving proof of concept projects to demonstrate the solutions business values
- Lead/mentor junior data scientists to develop and deploy complex modeling solutions from initial concepts to final deliverables
- Explore and leverage inhouse external and other opensource machine learning software/algorithms
- Contribute in enhancing SoFis risk model development code base by developing customized Python scripts or packages
- Collaborate with Model Risk Management team and Fair Lending team to demonstrate models are developed with high level rigor that satisfy Model Risk Management requirements Fair Lending requirements and other regulatory requirements
- Spearhead model deployment by collaborating with cross functional teams including Credit Product Engineering and Business Unit
- Present model performance and insights to Credit Risk and Business Unit leaders
- Investigating external data to identify trends in the market and industry
What youll need:
- 8 years of work experience in the related areas especially loss mitigation and loss forecasting with a Masters or PhD degree in Statistics Mathematics Economics Engineering Computer Science or a quantitative field.
- Excellent knowledge and experience of machine learning and statistical modeling methods for supervised and unsupervised learning. These methods include (but not limited to) regression clustering outlier detection novelty detection decision trees nearest neighbors support vector machines ensemble methods and boosting neural networks 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 knowledge of AI and AI safety
- 2 years of experience in leading and mentoring junior data scientists
- Strong programming skills in Python
- Strong knowledge of databases and related languages/tools such as SQL NoSQL Hive etc.
- Strong presentation skills: able to use data to tell a clear and compelling story; comfortable with public speaking across various forums including regulatory examinations and able to effectively and logically communicate when information is being challenged in an open forum.
- Ability and confidence to exercise influence over a wide range of individuals at different levels of technical and business leadership.
- 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:
- Experience in communicating with OCC Fed and CFPB
Why youll love working here: Please do not add additional company information or copy into the job description in Greenhouse. This info will automatically post there.
- Competitive salary packages and bonuses
- Comprehensive medical dental vision and life insurance benefits
- Generous vacation and holidays
- Paid parental leave for eligible employees
- 401(k) and education on retirement planning
- Tuition reimbursement on approved programs
- Monthly contribution up to $200 to help you pay off your student loans
- Great health & wellbeing benefits including: telehealth parental support subsidized gym program
*These benefits are only applicable to full time employees
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 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
Due to insurance coverage issues we are unable to accommodate remote work from Hawaii or Alaska at this time.
Required Experience:
Staff IC
Employment Type
Full-Time
