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Tech Stack
Tools & technologiesAWSPySparkPythonSQL
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- 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
Benefits
Comp & perks- 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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
statistical analysismachine learningstatistical modelingdata manipulationpredictive model developmentdata cleaningoutlier detectioncomplex logic creationmodel deploymentCI/CD pipelines
Soft Skills
analytical thinkingcommunicationcollaborationproblem solvingpresentation skills