Lead Data Scientist Job at Prism Data (NYC or San Diego (La Jolla/UTC))

Job Description

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. At the heart of Prism’s offering is Data Science—not just as a technical function, but as the core product. As such, the Lead Data Scientist 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 Lead Data Scientist who will make high-impact, hands-on contributions that sustain and advance Prism’s industry-leading position.

Job Responsibility

Maintain and advance existing analytical product suite
Enhance core cash flow underwriting offerings as new data elements become available
Develop next-generation versions of products to boost stability, predictive accuracy, and relevancy to emerging use cases
Develop new products for new market opportunities using novel data assets
Demonstrate best practices in transparent modeling approaches to enable easy client adoption
Support sales, revenue attainment, and thought leadership
Conduct proof of concept analyses of the efficacy of Prism products in the context of clients’ business problems, and present results and insights
Support new and existing clients by guiding them on score cutoffs and the use of powerful custom attribute sets for their business
Educate clients on technical product knowledge
Contribute analysis to thought leadership content delivered by Prism executives in white papers and industry conferences
Streamline technical operations
Support product implementations in the proprietary platform that powers the products and enables high performance
Monitor product performance to ensure stability and power
Identify issues and improvement opportunities
Ensure internal processes are scalable, repeatable, and continuously improving, especially with the proof of concept analysis process
Lead and communicate
Successfully improvise and handle new situations using judgment and expertise developed through experience
Own time and task management of assigned projects, some of which may include coordinating the contributions of others
Demonstrate exceptional oral, written, and interpersonal communication of complex technical information in a simplified manner to various audiences
Independently and effectively engage in cross-team discussions to direct deliverables, deadlines and handoffs

Requirements

Bachelor’s degree in Statistics, Data Science, Math, Industrial Engineering, or similar quantitative discipline required
Master’s or PhD is a plus
4+ years of experience as a Data Scientist or Statistician, preferably in credit risk or financial services
Research & development of new attributes, models, decision strategies, and/or analytic capabilities
Customer-facing testing of data or analytic solutions (e.g., credit risk scores, alternative data, fraud prevention, etc.)
Cash flow underwriting analytics experience is a strong plus
Collaboration with business teams to understand and address business problems
Modeling experience in the latest AI and machine learning approaches
Mastery of rudimentary modeling approaches (e.g., regression, decision trees)
Expertise building Gradient Boosting models is a plus
Experience with Natural Language Processing, Large and Small Language Models, and transformer models is a strong differentiator
Knowledge of data labeling/categorization, feature development and selection, model design and training, testing, coding, implementation, monitoring, and governance
Financial services industry data expertise, including types of data sources applicable to different types of business decisions based on regulatory factors
Experience evaluating alternative statistical approaches, including review of academic papers on new techniques and ideas, and justifying which approach is best suited for which problems and why
Ability to mentor and QA the hands-on work of junior data scientists
Languages: Python, SQL

Nice to have

Master’s or PhD
Cash flow underwriting analytics experience
Expertise building Gradient Boosting models
Experience with Natural Language Processing, Large and Small Language Models, and transformer models

What we offer

Equity-based compensation
Comprehensive benefit plan, including medical, dental, vision, and 401(k)

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