Sr Decision Science Analyst
Summary
Senior Decision Science Analyst applying analytics and predictive modeling to guide credit, fraud, and pricing decisions for TreviPay's B2B payments and invoicing platform, using SAS/Python and BI tools.
Every day, TreviPay employees are challenged and empowered in a supportive, collaborative, entrepreneurial environment.
Responsibilities
• Deliver and communicate high quality data-driven analyses to key stakeholders and senior management that provide key insights leading to actionable results.
• 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 for existing account management.
• 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.
• Analyze risk and pricing strategies, including the predictive models built for those strategies in Credit and Fraud.
• Monitor the results of risk and pricing strategies by evaluating performance relative to expectations.
• Develop monitoring tools to evaluate continued performance of both generic and custom models
• Support the development (or build yourself) of statistical models and other types of predictive models as appropriate to improve our Credit and Fraud risk position, for both application and portfolio risk.
Requirements:
• Bachelor’s Degree Required
• Minimum 6 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 and/or Python, MS Excel, Enterprise Reporting BI tools, 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 experience
- Competitive salary
- Paid parental leave
- Generous paid time off
- Medical, dental, vision, FSA, Life/AD&D, long and short term disability
- 401K matching
- Employee referral program
- in saying yes to unique and challenging requirements
- empowered team members are creative team members
- our products make the customer’s day just a little bit better
- work/life balance makes us all more effective
As published by lever
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