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TreviPay Senior Portfolio Analyst in Overland Park, Kansas

This job was posted by https://www.kansasworks.com : For more information, please see: https://www.kansasworks.com/jobs/12318736



At TreviPay, we help clients grow by streamlining B2B payments through a combination of innovative technology, service expertise, and working capital to improve their customer’s experience and free up funding for growth. We facilitate $6 billion in transactions per year in 18 currencies for customers in more than 27 countries. We specialize in payment and credit management for B2B companies across the globe, setting the stage for the future of omni-channel B2B payments by extending terms, handling invoicing and managing collections. We take care of our clients by taking care of their customers.




Every day, TreviPay employees are challenged and empowered in a supportive, collaborative, entrepreneurial environment.




Responsibilities


+ Access, cleanse, and analyze relevant internal and external data to support the creation and improvement of effective risk management and pricing strategy techniques across B2B new account origination, existing account management (e.g., credit line management, renewals, suspensions, pricing strategies, preapprovals, collections, roll rate analysis/loss provisioning, and fraud mitigation).


+ 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.


+ Apply statistical modeling methods to determine the potential impact of pricing strategies on profitability.


+ Collaborate with Sales and Marketing on developing and implementing competitive pricing strategies.


+ Develop/enhance Portfolio Risk Assessment reporting package detailing Key Risk Indicators, trends and projections for monthly and quarterly presentation to 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.


+ Support internal/external Data Scientists with subject matter expertise and clean, actionable datasets for the growth of predictive and advanced analytical capabilities including the use of machine learning, artificial intelligence, and traditional linear modeling and segmentation analysis.


+ Conduct statistical and non-statistical data exploration, data validation, and identify/address data quality issues through data analysis, data mining, and ad hoc/routine risk and pricing/profitability reporting.




Requirements:


+ Bachelor’s Degree Required


+ Minimum 5 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 SMB/B2B 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, 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 man agement, 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 is preferred


+ Statistical modeling experience (e.g., logistic regression, machine learning, etc.)


+ Prior leadership/management experience

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