Senior Financial Risk Analytics Architect

Santander US; Stamford (CT); On-site; USD 109,000 - 180,000; Full time

Job summary

Santander US is seeking a Senior Financial Risk Analytics Engineer to design, develop and maintain models and data workflows for CECL, reserving, stress-testing, and underwriting. You will partner with Finance, Risk, IT, and Data teams to deliver scalable analytical solutions that drive actionable insights.

The role requires deep SQL, SAS and Python skills, plus experience with large-scale data platforms and banking risk practices.

Qualifications

• Bachelor’s degree in a quantitative field. - Required
• 10+ years of experience with relational DBMS (Oracle/SQL) and analytics in banking. - Required
• 5+ years in modeling/quantitative analytics in financial services. - Preferred
• Proficiency in SAS and Python/R and data stream tooling. - Required
• Experience building large-scale data workflows and data pipelines. - Required
• Experience with CECL, stress-testing, underwriting, forecasting, or risk management. - Preferred
• Experience with cloud platforms and BI/reporting tools (Tableau/Qlik Sense). - Preferred

Responsibilities

• Research, scope, and manage business requirements for CECL models and related activities.
• Design, develop, and maintain analytical models and supporting infrastructure.
• Develop knowledge of Webster’s data systems, databases, and reporting environments.
• Build data workflows and automated processes for forecasting and risk management.
• Collaborate with IT, Data Management, Finance, Risk, and business partners.
• Create reports, dashboards, and visualizations to support decision-making.

Skills

SQL development

SAS

Python

R

Airflow

Tableau

Qlik Sense

Cloud platforms

Data modeling

Education

Bachelor's degree in a quantitative field

Master's degree preferred

Tools

Oracle

SQL

SAS

Python

Apache Airflow

Tableau / BI tools

AWS / Azure / GCP

Data pipelines

Job description

Santander US is seeking a Senior Financial Risk Analytics Engineer to design, develop and maintain models and data workflows for CECL, reserving, stress-testing, and underwriting. You will partner with Finance, Risk, IT, and Data teams to deliver scalable analytical solutions that drive actionable insights.

The role requires deep SQL, SAS and Python skills, plus experience with large-scale data platforms and banking risk practices.