Mandatory: solid foundation in statistics and quantitative methods — hypothesis testing, regression analysis, confidence intervals, and experimental design applied to business problems.
Mandatory: hands-on experience with A/B testing methodologies, experimentation frameworks, and interpreting statistical significance in a business context.
Experience with predictive modeling or propensity scoring techniques (logistic regression, decision trees, or equivalent).
Proficiency in translating data and statistical findings into strategic narratives and executive-level recommendations.
Familiarity with API integrations and connecting to external data sources.
Desirable but Not Essential
Knowledge of collections, credit risk, or lending operations.
Experience with agency management, vendor scorecards, or procurement analytics.
Familiarity with machine learning or statistical modeling for propensity scoring.
Experience in Fintech, financial services, or similarly data-driven industries.
Specific Knowledge
Experience in Data Science, Strategy, Business Intelligence, Analytics, or Collections Operations roles.
Strong understanding of portfolio management, delinquency tracking, and recovery strategies.
Ability to independently scope, execute, and communicate strategic projects with minimal supervision.
Tech Stack
Python
SQL
Benefits
100% Company-funded Health and dental and vision discount plan for employees and immediate family members.
Life insurance.
Phone finance, Headphone, home office equipment and wellness perks.