Hybrid Data Science Intern — ML & Credit Risk

Prism Data is building the future of credit risk assessment using modern data science and transaction-level financial data. Our API-based platform enables banks, fintechs, and lenders to use automated cash flow underwriting—analyzing detailed banking history in real time—to improve credit decisions, expand approvals, and reduce losses.

We believe cash flow tells a more accurate story than traditional credit scores alone, and we’re building products that help credit providers make faster, fairer decisions.

Prism transforms raw transaction data from any source into highly structured, explainable features and predictive risk scores, including the market-leading Cash Score®. Our products sit at the intersection of data engineering, machine learning, and regulated financial decisioning—and are trusted by some of the largest financial institutions and fastest-growing fintechs in the country.

Prism is well-funded and backed by leading strategic investors like Synchrony and Citi, along with top-tier venture firms including Obvious Ventures, Valar Ventures, and Core Innovation Capital.

At the heart of Prism’s offering is Data Science—not just as a technical function, but as the core product. As such, the Data Science team plays a uniquely central role in the company’s success, with direct influence on product innovation, commercial strategy, and company-wide decision making.

Prism is seeking a Data Science Intern to join its growing team. The team conducts R&D for next-generation solutions, tests and presents Prism products’ effectiveness at solving prospects’ and clients’ business problems, produces insights that inform external thought leadership, and collaborates with cross-functional partners to enhance operations. The role presents a rare opportunity to make a measurable difference at a critical inflection point for both Prism and the credit scoring and lending industries.

Train Models: Utilize your background in data science to build models to categorize transactions, identify income, and proactively identify credit risk.

Research: Research and evaluate new model development and training techniques. Determine applicability of new technologies to Prism’s business.

Evaluate: Explain to clients and prospects how they can get the most value out of Prism’s solutions.

Communicate: Explain technical concepts to clients and prospects with less experience in data science. Translate the statistical model performance into business value.

Bachelor’s degree in a STEM-related field.

Knowledge/interest in common data science/statistical tools and techniques.

Python programming experience.

Strong strategic thinking and analytical skills.

Excellent communicator and internal relationship builder, who can collaborate cross-functionally (e.g., with our sales, product and technical teams) on complex topics.

Ability to understand and explain technology and data flows.

A self-starter with a track record of success working with distributed teams.

This role is a temporary, hourly role, with the possibility to transition into a full time entry-level Data Scientist role in the fall. The role is 40 hours per week and pays $32.50 per hour.

Prism is an equal opportunity employer and values diversity. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws.

Prism is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. Please let us know if you need assistance with your application or interviews due to a disability.