TreviPay

Sr. Manager, Decision Science

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Hiring Remotely in Overland Park, KS, USA

In-Office or Remote

Senior level

Fintech • Software • Financial Services

The Role

Leads advanced analytics and predictive modeling for B2B credit risk, fraud, pricing, and profitability. Develops statistical models, supports risk model frameworks, monitors strategy performance, analyzes customer and market data, and produces portfolio risk reporting for executives. Partners cross-functionally with Risk, Product, Technology, Engineering, and Data Science teams while identifying data quality issues and delivering actionable insights.

Summary Generated by Built In

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 will leverage advanced analytics, predictive modeling, and data-driven insights to shape TreviPay's credit, fraud, and pricing strategies. Working closely with stakeholders across Risk, Product, Technology, and senior leadership, you'll transform complex data into actionable recommendations that improve portfolio performance, optimize customer outcomes, and support profitable business growth.

Responsibilities

· 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

Why you will love working at TreviPay

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

At TreviPay we believe:

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

TreviPay is an Equal Opportunity and Affirmative Action Employer. We welcome all veterans and disabled applicants.

Individuals with disabilities will be provided reasonable accommodation to participate in the job application and/or interview process. Please contact [email protected] to request an accommodation.

Skills Required

Bachelor's degree
At least 8 years of experience in a highly analytical environment performing complex business analysis and presenting data-driven insights
Strong knowledge of B2B credit or business banking credit risk, pricing, and profitability principles
Ability to extract, cleanse, merge, and analyze data from varied internal and external sources
Strong analytical and data simulation skills using SAS, Python, Microsoft Excel, Tableau, Sisense, or similar tools
Strong presentation skills and proficiency with Microsoft Word and PowerPoint
Experience analyzing data segments and identifying patterns, trends, or process improvements
Ability to create clear graphs, charts, reports, and presentations summarizing analytical results
Ability to collaborate cross-functionally with management, product, technology, compliance, and enterprise risk teams
Strong verbal and written communication skills
Bachelor's or master's degree in statistics, mathematics, or a similar quantitative field
Strong knowledge of B2B or business banking credit product pricing and profitability principles
Statistical modeling experience, including logistic regression, machine learning, and support vector machines
Prior leadership or management experience