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:
The 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.
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.