Data Scientist

ESSENTIAL FUNCTIONS:

To perform this job successfully, an individual must be able to perform each essential function at a high degree of proficient execution with little or no accommodation. The requirements listed below are representative, but not all inclusive, of the knowledge, skill, and/or ability required.

Conceive, design & monitor risk management strategies to improve business profitability in the areas of underwriting, credit line management, universe expansion and alternative data evaluation for lending
Participates in maintaining, developing, and implementing models includes design, development, validation, calibration, documentation, implementation, monitoring and reporting
Provides expertise to build and improve quantitative and qualitative models for various models (including CECL, Prepayment, Weighted Average Remaining Maturity (WARM), Probability of Default and Loss Given Default (PD/LGD) methodologies)
Compiles, analyzes, and resolves data errors/inconsistencies from various financial reporting systems
Collaborates with business groups to develop effective modeling approaches to accurately represent the risks for practical business use
Carries out regular model performance monitoring and produces comprehensive monitoring reports
Supports analysis and reporting in stress testing models
Develop credit policies for new lending products and iterate to improve underwriting criteria and loan amount/pricing strategies to maximize risk adjusted return and profitable revenue growth
Determine underwriting criteria using new credit risk models in partnership with our data and finance team
Set procedures to monitor risk and revenue of all credit products and performance across various lending partnerships
Use machine learning and performance by variable to dynamically segment applicants and loans based on behavior and performance
Recommend optimal segmentation strategy to build different models for different consumer segments
Optimize underwriting criteria, risk-based pricing strategy, and collection strategy by leveraging data analytics
Work with data team to track and analyze performance of various business and risk segments and programs to evaluate effectiveness
Write LookML and SQL queries and build dashboards in Looker
Supports ad hoc analytical projects, business analyses, and reporting

REQUIRED:

Bachelor's degree (required) or advanced degree (preferred) in a quantitative field (mathematics, statistics, computer science, engineering)
2+ years of experience in Data Science, Credit Risk, Fraud Risk, Quantitative Analytics, Operations Analytics, Modeling or related field
2+ years of relevant experience within consumer credit risk management, ideally at a FinTech startup or lending company; bonus points for healthcare experience prefer
2+ years of experience in designing and authoring reports/dashboards using Looker (and similar tools like Tableau, Power BI) is required
Preferred Experience in implementingDataPipelines leveraging Google Cloud products such as Cloud BigQuery, Cloud DataFlow, Cloud Pub/Sub, Cloud BigTable
Understanding of data warehousing concepts, design, modeling, data engineering
Work experience in Financial Services, preferably at a FinTech or consumer lending company, building risk strategies for several credit products (loans, lines of credit, credit cards). Experience in point-of-sale Healthcare a plus
Familiarity with bureau data and alternate data is a strong preferred
SQL experience, with programming experience in Python preferred
knowledge on Cash flow modeling and loss forecasting is a plus
Proven proficiency in basic statistics
Skilled in analyzing, interpreting and summarizing data

PatientFi jobs

Data Scientist