About Prism Data

About the role

The Lead Data Scientist at Prism Data plays a central role in sustaining and advancing the company’s industry-leading position. Reporting directly to the Head of Data Science, this role involves conducting R&D for next-generation solutions, testing and presenting Prism products' effectiveness, producing insights that inform external thought leadership, collaborating with cross-functional partners to enhance operations, and contributing to a growing team of data scientists.

Responsibilities

• 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

• Education: Bachelor's degree in Statistics, Data Science, Math, Industrial Engineering, or similar quantitative discipline required. Master's or PhD is a plus.
• Professional Experience: 4+ years of experience as a Data Scientist or Statistician, preferably in credit risk or financial services.
• Research & Development: Experience in developing new attributes, models, decision strategies, and/or analytic capabilities.
• Customer-Facing Testing: Experience in customer-facing testing of data or analytic solutions (e.g., credit risk scores, alternative data, fraud prevention, etc.).
• Cash Flow Underwriting Analytics: Cash flow underwriting analytics experience is a strong plus.
• Collaboration: Experience collaborating with business teams to understand and address business problems.
• Technical Skills and Knowledge: 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, experience with Natural Language Processing, Large and Small Language Models, and transformer models.
• Data Expertise: 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.
• Evaluation Approaches: 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.
• Mentoring and QA: Ability to mentor and QA the hands-on work of junior data scientists.
• Languages: Proficiency in Python, SQL.

Qualifications

• Education: Bachelor's degree in Statistics, Data Science, Math, Industrial Engineering, or similar quantitative discipline required. Master's or PhD is a plus.
• Professional Experience: 4+ years of experience as a Data Scientist or Statistician, preferably in credit risk or financial services.
• Research & Development: Experience in developing new attributes, models, decision strategies, and/or analytic capabilities.
• Customer-Facing Testing: Experience in customer-facing testing of data or analytic solutions (e.g., credit risk scores, alternative data, fraud prevention, etc.).
• Cash Flow Underwriting Analytics: Cash flow underwriting analytics experience is a strong plus.
• Collaboration: Experience collaborating with business teams to understand and address business problems.
• Technical Skills and Knowledge: 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, experience with Natural Language Processing, Large and Small Language Models, and transformer models.
• Data Expertise: 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.
• Evaluation Approaches: 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.
• Mentoring and QA: Ability to mentor and QA the hands-on work of junior data scientists.
• Languages: Proficiency in Python, SQL.

Benefits

Prism provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

Pay

Target base salary for this role is between $150,000 and $195,000 per year. Prism also offers additional equity-based compensation.

Equal Opportunity Employer

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.