16 дней назад
Senior Decision Science Analyst (Credit Risk)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Decision Science Analyst (Credit Risk/Predictive Modeling): Analyze B2B credit, fraud, pricing, and portfolio performance data to guide risk management and business strategy with an accent on predictive modeling, data quality, and strategy monitoring. Focus on building statistical and machine-learning models, evaluating model performance, and communicating actionable insights to senior stakeholders and cross-functional teams.
Location: Remote, based in the United States; listed location is Overland Park, Kansas
Company
provides a global B2B payments and invoicing network with eCommerce and ERP integrations, trade credit options, and accounts receivable automation.
What you will do
- Deliver data-driven analyses and communicate actionable insights to stakeholders, senior management, and cross-functional teams.
- Extract, cleanse, validate, and analyze internal and external data for B2B credit risk management and pricing strategies.
- Analyze and monitor credit and fraud risk strategies, predictive models, and portfolio performance against expectations.
- Develop monitoring tools for generic and custom models and identify data quality issues and improvement opportunities.
- Support the development of statistical and predictive models for application and portfolio risk.
- Partner with Engineering and Product teams to resolve roadblocks and interdependencies.
Requirements
- Bachelor’s degree and at least 6 years of experience performing complex business analyses in a highly analytical environment.
- Strong knowledge of B2B or Business Banking credit risk, pricing, and profitability principles.
- Experience extracting, cleansing, merging, and analyzing data from varied sources.
- Strong analytical and data simulation skills using SAS and/or Python, Excel, enterprise reporting BI tools, or similar packages.
- Experience identifying patterns, trends, and process improvements and presenting findings through clear reports, charts, and presentations.
- Strong communication, collaboration, multitasking, and stakeholder-management skills.
Nice to have
- Master’s degree or bachelor’s degree in Statistics, Mathematics, or a similar quantitative field.
- Statistical modeling experience with logistic regression, machine learning, SVM, or similar methods.
- Prior leadership experience.
Culture & Benefits
- Supportive, collaborative, and entrepreneurial work environment.
- Competitive salary and generous paid time off.
- Paid parental leave.
- Medical, dental, vision, FSA, life and disability insurance.
- 401(k) matching and an employee referral program.
- Emphasis on challenging requirements, employee empowerment, customer impact, and work-life balance.
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