At Freedom Financial, we are building leading information-based lending franchises. You will be part of a small team powering the continued growth of our FreedomPlus and ConsolidationPlus loan portfolios. As an analytic professional in our lending businesses, you will apply your strategic and analytical skills to address major company challenges. You will do it in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation.
This person must have excellent analytical capabilities in order to create accurate, thoughtful, clear recommendations that drive how we manage our business. Statistical Analysis, data mining, Advanced Excel, SQL skills, Machine Learning, highly effective communication skills, an entrepreneurial and proactive approach, exceptional time management and an ability to comfortably work with senior management are also critical for success in this role.
- Credit Risk Analysis:
- Analyze customer level information to determine the effectiveness of credit policies and recommend necessary changes to improve profitability
- Oversee and independently conduct quantitative analysis and analyze large volumes of data to identify emerging credit performance trends
- Develop and implement new product and pricing strategies for various lending products
- Leverage new data/processes to improve risk management strategies
- Leverage combination of following to drive actionable business insights: Financial modeling, SQL, statistical modeling (via SAS / R / Python / similar), hypothesis testing and forensic analysis
- Reporting: Design portfolio monitoring, processes, and controls for managing credit risk and identifying root causes of changes in loan performance
- Execution: Work with Product and Engineering teams to implement credit policy changes. Oversee multiple projects and programs concurrently
- Strategic & analytic orientation: A proven track record of decision-making and problem-solving based on analytics. Conceptual thinking skills must be complemented by a strong quantitative orientation, given that a large part of the business is based on rigorous analytic marketing & credit risk management
- Collaborate: with cross-functional partners in finance, operations, IT, compliance, etc. to develop and test hypotheses and achieve business objectives
- Communicate: Develop PowerPoint presentations that summarize your analysis and your recommendations. Present your findings to VP level Executives.
- Get it done: See your recommendations through from hypothesis, the proposal, to implementation. You will be expected to play an active role to drive your proposals all the way into implementation – you will be required to be hands-on to make this happen and ensure your proposals deliver desired business results.
Qualifications and Education Requirements:
- 4+ years of experience with unsecured or auto loan credit risk analysis focused on credit policy/pricing/loss forecasting
- Bachelor’s Degree in Engineering, Scientific field, Mathematics, Statistics, Finance, or Accounting
- Understanding of decision trees, segmentation, regression and other intelligent decision models used to analyze customer response behaviors, interaction patterns, and propensity
- Strong analytic problem-solving ability
- Ability to influence others
- Performance and results-driven
- Able to manage projects from start to finish
- Very strong MS Excel skills
- A minimum level of Math coursework: Calculus 1, Statistics 1 (math problem-solving skills required)
- 7+ years of experience in quantitative business analysis, data science, and/or statistical analysis;
- or relevant Master’s Degree / MBA with 5+ years of experience
- MBA or Master’s Degree in Engineering, Operations Research, Industrial Engineering, Scientific field, Mathematics, Statistics, Finance, or Accounting
- Prior experience in one or more of business analysis, statistical model building, SQL querying, consulting
- SQL querying skills
- Tableau for developing business reports
- Coursework in Statistical Programming, Simulation, Regression
- Knowledge of and ability to interpret Probability Distributions, Hypothesis Testing, Regression techniques like Logistic Regression, Confidence Intervals