Research Assistant Jobs

About The Position

Requirements

• 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 Haves

• 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

Responsibilities

• 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

Benefits

• 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
• Invites to Member events, and more!
• Personalized Mentorship Program
• Fully stocked kitchen (snacks & drinks)