Senior Data Scientist

Nova Credit•New York, NY

20d•$140,000 - $199,500•Hybrid

About The Position

The Senior Data Scientist role will be part of the Data Science team at Nova Credit, where you will play a crucial role in researching, designing, and developing 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 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, based in the New York Metropolitan Area.

Requirements

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
Fluency using Python and SQL

Nice To Haves

Experience with hypothesis testing
Experience using PySpark and Pola.rs
NLP and document fraud experience
Consumer credit risk knowledge

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 our 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.