Sr Decision Science Analyst

TreviPay•Overland Park, KS

About The Position

At TreviPay, we believe loyalty begins at the payment. Thousands of sellers use our global B2B payments and invoicing network to provide choice and convenience to buyers, open new markets and automate accounts receivables. With integrations to top eCommerce and ERP solutions and flexible trade credit options, TreviPay brings 40 years of experience serving leaders in manufacturing, retail and transportation. Every day, TreviPay employees are challenged and empowered in a supportive, collaborative, entrepreneurial environment. As a Senior Decision Science Analyst, you'll sit at the intersection of data, risk, and business strategy. You'll use analytics and predictive modeling to uncover insights, evaluate portfolio performance, and guide critical credit, fraud, and pricing decisions. Partnering with teams across the organization, you'll help solve complex business challenges, influence strategic initiatives, and deliver data-driven solutions that support growth while managing 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

Nice To Haves

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

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.