About Nova Credit
Nova Credit is a credit infrastructure and analytics company that enables businesses to grow responsibly by harnessing alternative credit data. The company leverages its unique data infrastructure, industry-leading analytics & FCRA-compliance to help lenders fill in the gaps that exist in traditional credit analytics. Nova Credit provides access to the fragmented universe of consumer financial data and transforms it into compliant, actionable risk analytics through a suite of solutions designed to increase conversion through expanded coverage, speed, and reliability. Nova Credit supports over 7,000 businesses including organizations such as HSBC, SoFi, Scotiabank, Appfolio, and Yardi. They were named in Forbes’ Fintech 50 in 2025 and Built In’s Best Places to Work, 2025.
Nova Credit offers a dynamic and inclusive work environment where you can meaningfully impact the lives of people historically excluded from the credit system. They value diversity, intellectual honesty, and innovation, and are committed to supporting their team members' professional growth and development.
The Opportunity
The Senior Data Scientist role will be part of the Data Science team at Nova Credit, playing a crucial role in researching, designing, and developing their global data science strategy. Applying critical thinking and analytical skills to data, traditional statistical modeling, and modern machine learning techniques, you will serve as a conduit to bring key functions together, including: data partnerships, risk and analytics, product, engineering, and customer success, to develop and implement core data systems. Working closely with customer-facing teams, you will demonstrate the strength of products and services through data analytics and insights. Ultimately, your role is to ensure that Nova Credit’s products deliver high-quality predictive risk signals; every initiative you work on will be crucial to the company’s success.
This is a full-time, NYC-based hybrid role (3 days per week in office on Mondays, Tuesdays, and Thursdays) reporting directly to the Head of Data Science.
Responsibilities
- Research and develop credit risk predictive models based on cross-border consumer performance data or bank transaction data.
- Research and develop bank transaction text classification models leveraging statistical models and/or large language models.
- Utilize bank transaction data to develop attributes for credit risk assessment, income verification, or other financial products.
- Research and develop models for document processing and tampering identification.
- Collaborate with the engineering organization to guide reliable deployments of data science products.
- Perform continuous research into new data sources, variables, and modeling methodologies.
- Develop and execute model monitoring solutions.
Required Skills and Qualifications
- 4+ Years relevant experience in data science, quantitative modeling, or machine learning.
- Relevant PhD or MS preferred (e.g., Data Science, Computer Science, Statistics, Applied Statistics, Operational Research).
- Fluency in generalized linear models & machine learning methods and tools; Preferred - Experience with hypothesis testing.
- Fluency using Python and SQL; Preferred - Experience using PySpark and Pola.rs.
- Preferred - NLP and document fraud experience.
- Preferred - consumer credit risk knowledge.
- Above all, the ability to break down new and complex problems into fundamental and solvable components.