The Role:

Are you passionate about using data to make informed decisions? Do you enjoy digging into large datasets, asking "why" before "how," and turning analytical work into recommendations that leadership acts on?  Do you thrive when given the autonomy to scope your own work and run with it? If so, we want you to join the Risk Data Analytics team at SoFi this summer.

As a Data Scientist Intern on the Risk Data Analytics team within Independent Risk Management (IRM), you'll work as a full-time member of the team, paired with a senior mentor, and own a meaningful end-to-end analytical project. Your work will contribute directly to how SoFi measures, monitors, and manages risk across risk stripes.

Who You Are:

Risk analytics is a job of judgment under ambiguity. The data is messy, the questions are open-ended, and the recommendations land in front of senior leaders who act on them. That mix rewards a specific set of habits and values. You'll fit well on this team if you're:

• Entrepreneurial:
  • You move fast, make decisions, and pivot as new information lands. You look for creative solutions, aren't afraid to fail forward, and believe in continuous learning.
• Quantitative:
  • You think in terms of probability and base your judgement on sound statistical principles applied in a business context.
• Qualitative:
  • You explore data to understand the "why" before jumping to the "how," and you bring narrative and judgment to the numbers.
• Act as founders:
  • You own your work end-to-end and make your footprint bigger than your foot. You check in when it matters and figure things out when it doesn't.  

What You’ll Do:

• Own an end-to-end analytical project from scoping through final leadership memo, with guidance from a senior mentor
• Partner with stakeholders across Risk, Compliance, and the business lines to translate open-ended questions into structured analytical approaches
• Explore large datasets using SQL and Python to identify patterns, anomalies, and statistical relationships
• Apply the right statistical and machine-learning methods to the problem; from hypothesis testing and regression to classification and causal-inference techniques
• Build production-quality data pipelines using dbt and Snowflake so your analysis can be refreshed, monitored, and used over time
• Create Tableau dashboards, Streamlit or React applications, and other artifacts that make your analysis usable by leaders and operators
• Write clear, concise documentation that explain what you did, what you found, and what you recommend
• Present your findings to technical and non-technical audiences, including senior leadership
• Learn new tools, technologies, and domain concepts quickly; risk analytics in financial services is a deep space, and you'll be developing both your technical and contextual knowledge throughout the summer

What You’ll Need:

• Enrolled in an accredited US-based university (working towards a Bachelor's or Master's degree) with an expected graduation date of December 2026 or Spring 2027
• Must be returning to school for at least one quarter or semester after the internship
• Have no more than 12 months of professional full-time work experience (excluding internships and research assistant roles)
• Must be willing to relocate to San Francisco Bay Area and be available to work in the San Francisco office at a hybrid capacity (2-3x a week)
• Proficiency in SQL and Python
• Solid foundation in probability and statistics, including hypothesis testing and regression
• Experience analyzing datasets and identifying trends, patterns, and anomalies; ideally in a non-academic setting (internship, research role, or substantive project)
• Strong written and verbal communication skills; the ability to explain technical work clearly to non-technical audiences
• Intellectual curiosity and the drive to push through ambiguity to a clear, defensible answer

Nice to Have:

• Academic background in Software Engineering, Economics, Statistics, Finance, or a related quantitative field
• Exposure to machine-learning techniques relevant to risk analytics, such as anomaly detection, classification on imbalanced data, or NLP
• Familiarity with dbt, Tableau, Snowflake
• Experience using AI / agentic tools beyond ChatGPT 
• Prior exposure to financial services, compliance, or other regulated industries

Internship Perks:

• Access to senior leadership, including exclusive Q&A sessions with executives across all functions of SoFi
• Exclusive opportunities to deliver a case study to SoFi leaders 
• Development sessions for career, financial, and professional growth
• Opportunities to participate in company wide events like All-Hands and SoFi circles programming
• Networking socials to connect with fellow interns
• SoFi swag giveaways
• We offer incoming interns the flexibility to select from two potential start dates:
  • Cohort 1: Monday, June 1st, 2026 to Friday, August 21st, 2026
  • Cohort 2: Monday, June 15th, 2026 to Friday, September 4th, 2026