Stamford, CT, USA
27 days ago
Quant Engineer, Finance Analytics, Director

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 ResponsibilitiesResearch, 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 & Experience10 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 & Experience5-10 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 PipelineFull 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.

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.

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