Data Scientist/Senior Data Scientist
New York, NY, USA
Posted on Thursday, April 6, 2023
At Nova Credit, our mission is to power a more fair and inclusive financial system for the world. Nova Credit’s diverse global team is stitching together the world's credit data into a single network to unlock financial opportunities for immigrants and other populations historically excluded from the credit system. We’ve built a platform that enables lenders to access a single, predictive cross-border credit database to help enable underwriting decisions. We are backed by leading investors, including Kleiner Perkins, General Catalyst, and Index Ventures, and are proud recipients of the following awards:
- Forbes’ Best Startup Employers 2022
- BuiltIn NYC's Best Places to Work 2022: Best Small Companies to Work For
- Fast Company’s World’s Most Innovative Social Good Companies 2022
The Data Scientist/Senior Data Scientist role will be part of the Data Science team within Nova Credit, where you will play an essential role in researching, designing, and building out our global data science strategy. Applying your 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 our core data systems. Working closely with our customer-facing teams, you will demonstrate the strength of our 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 critical for the company’s success!
Note: this posting is for two full-time roles reporting to our Directors of Data Science on the Credit Passport or Cash Atlas teams. Remote candidates anywhere in the contiguous U.S. are welcome to apply. We are open to candidates at both the Data Scientist and Sr. Data Scientist levels for this particular posting.
Credit Passport Team:
- Develop consumer credit risk predictive models based on cross-border consumer performance data to predict the likelihood of default;
- Build score mapping algorithms to transform from outbound bureau scores to inbound market equivalent scores;
- Perform ongoing performance data monitoring and present business insights to management;
- Work with cross-functional teams to address business problems and ad-hoc requests to support our Customer Success team;
- Collaborate with our engineering organization to standardize data from various bureaus and integrate new bureaus in partnership; manage data quality/integrity checks and conduct UAT
Cash Atlas Team:
- Develop algorithms to unify bank transaction data from multiple banks and data vendors;
- Use bank transaction data to research and create variables used for credit risk modeling;
- Develop credit risk models for underwriting consumers with and without credit scores;
- Develop account monitoring solutions using traditional credit information and bank information;
- Collaborate with our engineering organization to guide reliable deployments of data science products;
- Perform continuous research into new data sources, variables, and modeling methodologies
- 2-4+ Years Experience (depending on level) in data analytics, statistical modeling, or machine learning
- Experience in logistic regression & Machine Learning methods and tools
- Experience using Python, R, and SQL
- Consumer credit risk knowledge is preferred
- Relevant Ph.D. or MS preferred (e.g., Data Science, Computer Science, Statistics, Applied Statistics, Operational Research)
- Above all, critical thinking skills, creativity, an open mind, and curiosity to explore complex data to extract usable information and insights!
Everyone is welcome at Nova Credit. We are an equal-opportunity employer where our diversity and inclusion are central pillars to our company strategy. We look for applicants who understand, embrace, and thrive in a multicultural and increasingly globalized world. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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