Independently deliver analytical projects across the consumer credit lifecycle, including acquisition, account management and collections
Build statistical and machine learning models through all phases of development, from design through training, evaluation, validation and implementation
Use a broad set of technologies: SQL, PySpark, Python, AWS and more to obtain insights from large volumes of data
Design and improve acquisition strategies, including segmentation, decision rules, and cut-off strategies
Translate findings into applicable business recommendations for partners
Collaborate with internal and external clients to determine the appropriate analysis parameters and performance measures to be applied, as well as requirements for decision tool and strategy implementation and monitoring.
Interpret results of analyses, identify trends and issues and recommend alternatives to support our goals.
Communicate with and deliver presentations to end-users on analysis results.
Produce implementation plans and participate in audits to help implement statistical models and other decision tools.
Help develop analytic and data products and services, and the enhancement of current processes and offerings.

Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field
8+ years' experience with statistical and quantitative analysis, Machine Learning, Statistical Modeling including large-scale data manipulation in Credit Lending industry
Proficiency in Python (required) and SQL, with experience building scalable pipelines
Knowledge of statistical models and practical experience in predictive model development (Python, R, SAS).
Domain experience in financial services, with exposure to credit lending, credit risk modeling, and credit decisioning lifecycle (e.g., origination, underwriting, limit setting, portfolio monitoring)
Experience with model deployment and productionization, including CI/CD pipelines, version control, and integration of models into scalable, real-time or batch decisioning systems
Experience joining large datasets from multiple data sources, creating complex logic for data cleaning, outlier detecting, and refining business rules to validate and monitor the model forecast
Experience solving complex and unique problems

Flexible Time Off: 20 Days
Great compensation package and bonus plan
Core benefits including medical, dental, vision, and matching 401K
Flexible work environment, ability to work remote, hybrid or in-office
Flexible time off including volunteer time off, vacation, sick and 12-paid holidays

Senior Data Modeling Analyst

Key skills