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!
The Senior Analyst, Portfolio Analytics & Credit Research will enhance the Credit organizations quantitative analytical capabilities assisting in building bottoms-up, credit stress testing framework and dual risk framework. Enhance portfolio monitoring capabilities through use of sophisticated analytics, statistical analyses and process automation.
Support Portfolio Analytics in preparing Portfolio Quality Reviews, (PQR's) and other monthly/quarterly analytics on various business segments throughout the Bank. Provide detailed analysis of both internal Bank data as well as benchmark third party data, coupled with macro-economic and industry research. Support strategic initiatives and credit risk management activities as assigned.
Utilize advanced programing skills such as Python, SQL, R and other advanced code writing to enhance Bank portfolio analytics. Recommend, develop, test and train artificial intelligence models for implementation.
Responsibilities
Support Portfolio Analytics and Credit Research Team in everyday business functions such as Portfolio Quality Reviews (PQR's), Portfolio Stress Testing, and general credit, macro-economic research and sophisticated analytics.
Collect data sets from multiple sources within the Bank, reconcile and prepare baseline clean data for analysis.
Incorporate advanced programming such as Python, SQL, and other Machine Learning (AI) programs to collect and produce advanced multi-dimensional analytics for various loan portfolios on a quarterly or ad-hoc basis.
Support benchmarking analytics, which includes analysis ranking performance on size, concentration, reserves, delinquencies, and overall performance. Additionally, assess Webster key performance metrics against third party sources such as Trepp, Co Star, LCD, etc.
Provide data stewardship of third-party benchmarking data sources as well as associated API's
Maintain digital delivery of third-party benchmarking data feeds on a monthly basis
Where appropriate, introduce statistical and/or machine learning (AI) techniques to advance data collection and analytic capabilities of overall team
Write code for API integration/data collection for licensed WBS data platforms such as Trepp, Placer AI, and Rockport VAL
Research and introduce data visualization software/methods that integrate with coding platforms and could be used to generate graphs/charts for presentations (non-excel methods -- i.e. Matplotlib Python)
Support dual risk rating framework and process build.
Other portfolio analytics and ad hoc initiatives as assigned.
Experience
BA or BS in Finance, Economics, or Data Analytics required.
Masters Degree with a quantitative concentration preferred.
2 - 4 years applicable experience in financial modeling, statistical analysis, data analytics, programming, machine learning models & AI coding.
Experience with machine learning algorithms such as XG Boost and Random Forest
Advanced Excel (i.e. Macros, financial formulas, VBA), SQL, Python, R, OpenAI, PowerPoint, and Word
Strong analytical skills and ability to multitask with multiple projects on timelines.
Excellent oral and written communication skills, and ability to express ideas to senior management.
Ability to apply quantitative techniques in order to analyze portfolio risks
Ability to analyze massive data sets over various bank portfolios
Good interpersonal skills.
Exceptional leadership and organizational skills.
The estimated salary range for this position is $90,000USD to $110,000USD. 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.
