Develop statistical models and other types of predictive models as appropriate to improve our risk position (both fraud and credit), pricing strategies, and profitability.
Support the creation of a Model Development Framework, documenting the approach the Risk Management team will use so that we incorporate a consistent, stable modeling process at Trevipay
Monitor the results of risk and pricing strategies by evaluating performance relative to expectations.
Analyze customer usage, competitor pricing and market trends to increase market share and profitability.
Access, cleanse, and analyze relevant internal and external data to support the creation, monitoring, and improvement of effective B2B credit risk management and pricing strategy techniques across new account origination and existing account management.
Develop/enhance the Portfolio Risk Assessment reporting package detailing Key Risk Indicators, trends, and projections for presentation to the executive leadership team.
Deliver and communicate high quality data-driven analyses to key stakeholders and senior management that provide key insights leading to actionable results.
Conduct data exploration, data validation, and data audits to identify and address data quality issues and recommend improvements.
Support Engineering and Product teams with resolution of roadblocks and interdependencies.
Support internal/external Data Scientists with subject matter expertise and clean, actionable datasets for the growth of predictive and advanced analytical capabilities.
Requirements
Bachelor’s Degree Required
Minimum 8 years of proven work experience in a highly analytical environment performing complex business analyses, generating data-driven insights and presenting findings to leadership and other stakeholders.
Strong knowledge of B2B credit and/or Business Banking credit risk, pricing, and profitability principles
Ability to deal with ambiguity and be flexible enough to shift workload in accordance with changing priorities.
Ability to extract, cleanse, merge and analyze data from varied internal and external sources.
Strong analytical and data simulation skills including SAS, Python, MS Excel, Tableau/Sisense, or similar analytical and reporting/data visualization packages.
Strong presentation skills and proficiency in MS Word and PowerPoint
Experience in analyzing segments of data or utilizing tools to identify and explain patterns, trends and/or process improvements
Ability to create clear, concise graphs, charts, reports and presentations summarizing analytical results and justifying suggested improvements
High performing contributor with ability to collaborate cross-functionally with management, product, technology, compliance and enterprise risk
The ability to multitask in a fast-paced environment
Strong communication skills, both verbal and written
Preferred Qualifications:
Bachelor’s or Master’s Degree in Statistics, Mathematics or similar quantitative field of study
Strong knowledge of B2B and/or Business Banking credit product pricing and profitability principles
Statistical modeling experience (logistic regression, machine learning, SVM, and more)
Prior leadership/management experience
Tech Stack
Python
Tableau
Benefits
Competitive salary
Paid parental leave
Generous paid time off
Medical, dental, vision, FSA, Life/AD&D, long and short term disability