Manager of Data Science & Analytics
About The Position
Deliver advanced analytical solutions using advanced statistical and machine learning techniques to drive optimized business outcomes. Play a key role within a small close-knit team, assuming full responsibility for the day-to-day administrative, operations, compliance, sales leadership, growth, performance, and profitability of a branch office. Be involved in a managerial training program to enhance skills and encourage internal advancement. Collaborate with Credit Risk, Marketing, Branch Operations, Account Management, and other functions to identify specific business problems to address. Partner with business teams to help with Design of Experiments (DOE) and successful incorporation of the solutions into business strategies. Perform exploratory analysis or leverage the analysis shared by the business functions to brainstorm various advanced analytical solutions. Build highly adoptable and efficient data pipelines. Perform data extraction, standardization, transformation, and further data wrangling to prepare the data to apply advanced machine learning or statistical techniques. Apply advanced machine learning and statistical techniques to develop, validate, deploy, and monitor/maintain predictive models. Create and maintain a comprehensive model documentation in a centralized location. Use traditional credit bureaus and other alternative consumer credit data for building consumer lending models such as: Probability of Marketing Response, Probability of Loan Default, Loss Given Default, and CECL Loss Forecasting. Present model development packages and results to executives and senior managers. Seek the approval for implementation by presenting compelling business benefits from the solutions. Work with IT and ensure successful deployment of solutions in the decision engine, including data mapping, providing requirements for data parsing/storage, validating scoring models in production, and troubleshooting to resolve issues. Create model governance packages once a quarter to monitor stability of the predictive models and share with executives and senior leaders.
Requirements
- Master's degree in Engineering, Data Analytics, Data Science, Computer Science, or related technical field required.
- Five years of experience in consumer lending required.
- Any experience required with: Python, SQL, and a data visualization program (i.e., Tableau, Power BI); delivering innovative/effective solutions to address business problems; handling and processing large datasets; working with data processing frameworks; building reliable data pipelines; building advanced analytical solutions using best-in-class machine learning and statistical modeling techniques (i.e., Random Forest, Gradient Boosting, LASSO, Elastic Net); supervised and unsupervised learning techniques; working with data from various bureaus and third-party data providers; and with structured, semi-structured, and unstructured data.
- Must have legal authority to work in the U.S. EEOE.
Responsibilities
- Deliver advanced analytical solutions using advanced statistical and machine learning techniques to drive optimized business outcomes.
- Play a key role within a small close-knit team, assuming full responsibility for the day-to-day administrative, operations, compliance, sales leadership, growth, performance, and profitability of a branch office.
- Be involved in a managerial training program to enhance skills and encourage internal advancement.
- Collaborate with Credit Risk, Marketing, Branch Operations, Account Management, and other functions to identify specific business problems to address.
- Partner with business teams to help with Design of Experiments (DOE) and successful incorporation of the solutions into business strategies.
- Perform exploratory analysis or leverage the analysis shared by the business functions to brainstorm various advanced analytical solutions.
- Build highly adoptable and efficient data pipelines.
- Perform data extraction, standardization, transformation, and further data wrangling to prepare the data to apply advanced machine learning or statistical techniques.
- Apply advanced machine learning and statistical techniques to develop, validate, deploy, and monitor/maintain predictive models.
- Create and maintain a comprehensive model documentation in a centralized location.
- Use traditional credit bureaus and other alternative consumer credit data for building consumer lending models such as: Probability of Marketing Response, Probability of Loan Default, Loss Given Default, and CECL Loss Forecasting.
- Present model development packages and results to executives and senior managers.
- Seek the approval for implementation by presenting compelling business benefits from the solutions.
- Work with IT and ensure successful deployment of solutions in the decision engine, including data mapping, providing requirements for data parsing/storage, validating scoring models in production, and troubleshooting to resolve issues.
- Create model governance packages once a quarter to monitor stability of the predictive models and share with executives and senior leaders.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
