Data Scientist
Webster Bank

Job Info

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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!

Data Scientist (Sr. Quantitative Analyst)

The Data Scientist role resides within FP&A supporting the CFO and senior leadership in fulfilling their oversight roles by independently assessing the Bank's performance and opportunity vs risk profile. The FP&A team leads the Bank's review and forecast of financial performance, reserving, stress-testing, annual budgeting process, operating plan variance analysis, profitability analysis, new business opportunities and special projects. Within FP&A, the Finance Analytics Solutions Team (FAST) designs, develops runs, maintains, and manages all analytical aspects of reserving, stress-testing & underwriting models.

Position Summary

The Data Scientist role involves gathering and understanding business requirements, model purpose and use; applying sophisticated statistical analysis to large data sets to satisfy business requirements; designing coding and maintaining new and existing models; anticipating and resolving challenges to model design & use; participating in model documentation and validation; and clearly communicating results. The scope of the role includes internally developed consumer and commercial credit models used for CECL/loss-reserving, stress-testing, and underwriting. The primary job function is to collaborate with Finance, Risk, Credit, Treasury, IT and LoB partners in developing source code implementing predictive analytical models to forecast losses & profitability, inform credit decisions and increase revenue.

Primary Responsibilities

• Support the Business Credit Center by maintaining models that drive credit decision automation.
• Proactively seek improvements to the credit models that increase the percentage of new loan application volume that can benefit from automated decisioning versus manual underwriting.
• Oversee the utilization of credit models used by or within other applications such as PowerLender, Sageworks, or similar workflow tools.
• Ensure adherence to Model Risk Management guidelines including maintenance of model documentation, change control, model reviews and validations as required.
• Create model output reporting that demonstrates model effectiveness to senior leadership in terms of decisions made over time.
• Develop, implement, maintain, and run models to support the Bank's loss-reserving/CECL, stress-testing, and underwriting decisioning, internal reporting and regulatory filings.
• Develop, implement, maintain, and run models for predicting business trends and providing analyses that drive business decisions and business planning.
• Develop expert knowledge and experience with Webster's data systems andtools
• 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, Treasury, Credit, Risk & IT partners, ensuring support requirements are met.

Required Skills & Experience

• A minimum of 3 years of modeling/analytical experience within a commercial bank or financial institution.
• Solid knowledge of statistical theory, including general linear models, categorical data analysis, and time-series estimation.
• Expert knowledge and skills in statistical programming languages: SAS, Python
• Ability to apply methods to real-world problems.
• Experience working with complex data structures within a RDMS (Oracle, SQL).
• Strong working knowledge with standard office tools such as Excel/VBA, PowerPoint, and Word
• Business knowledge and familiarity with small business/commercial banking products, operations, and processes.
• Ingenuity, analytical thinking, resourceful, persistent, pragmatic, motivated and emotionally intelligent.
• Time management skills and an ability to prioritize multiple tasks.
• Good communication skills (both verbal and written) and ability to multitask.
• 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

Preferred Skills & Experience

• Familiarity with underwriting and credit criteria applied in making credit decisions.
• Experience in developing constructive relationships with a wide range of stakeholders.
• Awareness of FICO scores and dual risk rating credit scoring approaches utilized by credit models.
• Model development or validation experience with loss-reserving, stress-testing, or underwriting.
• Significant skill & experience with financial risk modeling within a financial institution.
• Experience with common bank systems such as Moody's Data Buffet, SNL, and Bloomberg.
• Proficient with one or more cloud-based computing platforms: AWS, Azure, etc.
• Full stack software development experience.
  
  

Education

• Bachelors, Masters' or Ph.D. degree in econometrics, 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.

Position Location: Waterbury, Southington, Hartford or Stamford, CT

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