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.
SoFi's Data Science team is seeking an experienced Senior Staff Data Scientist to help lead our machine learning efforts. This individual will be responsible for the end to end development and deployment of machine learning models that improve SoFi's product experience for our members. You will build systems to recommend products to our members, improve conversion with personalization, and build models to better understand our member's behavior. The ideal candidate has a deep understanding of machine learning algorithms, strong programming skills, and a proven track record of driving successful data science projects from conception to deployment.
- Work closely with Product and Engineering partners to define product experiences that can be improved with machine learning
- Architect and deploy machine learning pipelines and infrastructure in AWS Sagemaker and Snowflake Snowpark
- Conduct advanced statistical analyses and machine learning experiments to extract actionable insights from large, complex datasets
- Collaborate with cross-functional teams, including product management, engineering, and business stakeholders, to define and prioritize data science initiatives
- Develop and maintain best practices for machine learning model development, deployment, and monitoring
- Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner
- Stay abreast of the latest developments in Data Science, Machine Learning, and AI, and apply this knowledge to improve our solutions
- 8+ years of experience in Data Science and machine learning, with a focus on developing and deploying machine learning models
- Track record of deploying user facing ML features in production
- Strong programming skills in Python with experience in machine learning libraries and frameworks
- Proficiency in data manipulation and analysis using SQL and data visualization tools
- Experience with cloud-based platforms and services for machine learning (eg AWS Sagemaker, Snowflake Snowpark)
- Strong communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams
- Ability to lead and mentor junior data scientists and engineers
- Advanced degree (Master's or PhD) with a quantitative major such as Statistics, Mathematics, Engineering, or Computer Science
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 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 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 [email protected].
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
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.
Top Skills
What We Do
For nearly a decade, SoFi has helped transform the Fintech industry by creating financial products and services that help people borrow, save, spend, invest, and protect their money better, so they can achieve financial independence and realize their ambitions. Whether it’s owning a home, saving for retirement, paying off their student loans, or helping our members invest - SoFi is there every step of the way. Want to learn more about how it works? Check it out here: https://www.sofi.com/how-it-works/
Our core values are at the center of how we help our 2+ million members get their money right. They are our guiding principles for how we think about serving our members, building our company, and most importantly, how we work together. At SoFi, it’s not just what we do - but how we do it.
SoFi is also proud to be the naming rights partner of SoFi Stadium, home of the Los Angeles Chargers and the Los Angeles Rams.
For more information, visit SoFi.com
Why Work 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 2+ million members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront.
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SoFi Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
You can work from anywhere! We take a flexible approach to the workplace, allowing employees to choose to be remote, hybrid, or in-office full time.