Prism Data Technologies, Inc. seeks a Data Scientist for its New York, NY location. Duties: Perform sophisticated financial and statistical analysis of bankcards and loan portfolios to generate data insights relating to spend and income patterns. Develop statistical and machine learning-based models to predict and estimate the risk profile of applicants by analyzing categorical spend and income transactions using deposit statement data. Write effective, low latency code to perform data analysis. Apply machine learning techniques and algorithms such as linear and logistic regression, gradient boosting, neural networks, clustering, feature engineering etc. Extract and analyze data, investigate data integrity, generate metrics, and perform ad hoc analysis. Partner with data engineers to validate and deploy solutions to a real time scoring environment. Run back tests on bank client data to showcase proof-of-concept model is stable and has value. Present proof-of-concept model performance and other value-add model performance and results to clients. Collaborate and brainstorm with product team to develop new products using deposit statement data as well as tweak existing products which improve efficiency or quality of insights and analysis they provide to the client. Work with the engineering team to implement models developed by data science team into production and ensure stability of these implemented models. Implement state of the art solutions in a real time scoring environment. Use programming languages such as Python, R, SQL, etc. and common data science toolkits such as Pandas, Numpy, Scikit Learn and Tensorflow to research and develop new statistical and machine learning models and improve existing models and techniques used in credit scoring products. Apply knowledge of credit lending space and credit risk to understand client’s business needs, definition of technical terms and metrics used in dataset. Requirements: Must possess a Master’s degree in statistics, mathematics or a closely related quantitative field plus three (3) years of experience in credit risk analysis. Alternatively, will accept a Bachelor’s degree in statistics, mathematics or a closely related quantitative field plus five (5) years of progressive post-baccalaureate experience in credit risk analysis. Must have at least one (1) year of experience with credit card analytics. Prior work experience must include: Quantitative and statistical modeling, data engineering, machine learning modeling, numerical analysis and data analytics related to consumer financial transaction data using AWS, Python, SQL, and python data science toolkits; Presenting results to non-technical audience, translating the statistical benefit of a model into business value; Working with software development teams to implement code and test to ensure that development and deployment results match. May work remote 100% of the time. Salary is $149,350 per year to $178,000 per year; 40 hrs/wk; Qualified Applicants must send resumes to careers@prismdata.com ref: DS/SN. Direct applicants only.

Minimum Salary: 149,350 Maximum Salary: 178,000 Salary Unit: Yearly