Quant Engineer

If you’re looking for a meaningful career, you’ll find it here at Webster. Founded in 1935, our focus has always been to put people first--doing whatever we can to help individuals, families, businesses and our colleagues achieve their financial goals. As a leading commercial bank, we remain passionate about serving our clients and supporting our communities. Integrity, Collaboration, Accountability, Agility, Respect, Excellence are Webster’s values, these set us apart as a bank and as an employer.  

Come join our team where you can expand your career potential, benefit from our robust development opportunities, and enjoy meaningful work!

Primary Responsibilities

• Research, dimension, and manage the scope, nature, business implications, workflow, data, personnel and time requirements for development, implementation, and maintenance of CECL credit loss models to support the Bank’s stress-testing, regulatory reserving, and underwriting.
• Personally participate in the development, coding, implementation, and maintenance of models.
• Develop expert knowledge and experience with Webster’s data systems and tools.
• Maintain rigorous work papers during the model development process. Author reports documenting the design, development, testing and use of new models, and changes to existing models.
• Develop strong relationships with Webster lines of business, Finance, Risk & IT partners, ensuring software development and support requirements are met.
• Lead and/or participate in Model Risk Management, Executive Management, Audit, Regulatory, and inter-departmental strategic and tactical planning & progress meetings.

Required Skills & Experience

• 10 or more years of experience working with complex data structures within a RDMS (Oracle, SQL).
• 10 or more years of software/data engineering experience within a commercial bank or financial institution.
• Experience in designing efficient and robust data workflows (e.g.- Apache Airflow).
• Knowledge in Reporting and Dashboarding tools (e.g.- Tableau, Qlik Sense).
• Proficient in Python/SAS/R Programming Language.
• Experience with design, coding, and testing patterns as well as engineering software platforms and large-scale data infrastructures.
• Knowledge with commercial & consumer banking products, operations, and processes.
• Ingenuity, analytical thinking, resourceful, persistent, pragmatic, motivated and socially intelligent.
• Time management skills are needed to prioritize multiple tasks.
• Documenting requirements as well as resolving conflicts or ambiguities.
• Excellent communication skills to convey complex technical concepts to non-technical stakeholders.
• Technically oriented, proactive, and enthusiastic, with good attention to details.

Preferred Skills & Experience

• 5-10 years of modeling/analytical experience within a commercial bank or financial institution.
• Proficient with one or more cloud-based computing platforms: AWS, Azure, GCP.
• Knowledge of statistical theory, in particular general linear models, categorical data analysis, time-series estimation, algorithmic optimization, supervised and unsupervised machine learning.
• Experience in CI/ CD Pipeline
• Full stack software development experience.
• Experience in developing constructive relationships with a wide range of different stakeholders.
• Ability to independently gather data from various sources and conduct research.
• Ability to think “out of the box” and provide suggestions on ways to improve the process.

Education 

• Bachelors, Masters’ or Ph.D. degree in Computer Science, Statistics, Data science or other STEM fields (e.g., physics, math, engineering, etc.) Finance or Business MS/MBA with strong quantitative and programming background also acceptable.

The estimated salary range for this position is $155,000USD to $170,000USD. Actual salary may vary up or down depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position is eligible for incentive compensation.

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.