Senior Decision Science Analyst

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.

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 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 to improve our Credit and Fraud risk position, for both application and portfolio risk.

Requirements:

• A Bachelor’s Degree is 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 the 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:

• A Bachelor’s or Master’s Degree in Statistics, Mathematics, or a 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.