Director Quant Engineer, Finance Analytics

Webster Bank•Stamford, CT

1d•$150,000 - $170,000

About The Position

The role involves gathering and understanding FP&A business requirements; Webster's data systems and tools; designing coding and maintaining data workflows; anticipating and resolving data challenges; user-friendly reports and dashboards; and clearly communicating results. The individual needs to collaborate with IT, Data Team, and LoB partners in developing data workflows, data analysis and reporting. The scope includes working across one or more of our main verticals: R&D, Quarterly Production, and/or Credit Scorecards. The Quant Engineer role is right for you if you're a "hands-on" coder and analyst, who takes ownership and puts the business first. Job Description Summary 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, and Excellence are Webster’s values that set us apart as a bank and as an employer. Come join our Financial Planning & Analysis (FP&A) team, where you can expand your career potential, benefit from robust development opportunities, and enjoy meaningful work. We are seeking a Director, Quant Engineer, Finance Analytics to serve as a key technical leader responsible for designing, developing, and maintaining data workflows, analytical solutions, and reporting capabilities that support critical FP&A initiatives. This role requires a hands-on engineer and analyst who can effectively partner with Finance, IT, Data Management, Risk, and business stakeholders to translate business requirements into scalable data and analytics solutions. The successful candidate will leverage Webster’s data systems and tools to support key functions including Research & Development (R&D), Quarterly Production, and Credit Scorecards while driving innovation, automation, and operational excellence across the FP&A organization.

Requirements

10+ years of software engineering, data engineering, analytics, or quantitative modeling experience within a commercial bank or financial institution.
Strong experience working with complex relational databases and large-scale data structures using Oracle, SQL, or similar technologies.
Advanced proficiency in Python, SAS, and/or R programming languages.
Experience designing, implementing, and maintaining efficient and scalable data workflows.
Experience with workflow orchestration tools such as Apache Airflow or similar platforms.
Strong understanding of software development lifecycle methodologies, coding standards, testing frameworks, and deployment practices.
Experience building analytical solutions supporting financial, credit risk, forecasting, or reporting functions.
Knowledge of commercial and consumer banking products, processes, and operations.
Strong analytical, problem-solving, and critical-thinking capabilities.
Demonstrated ability to manage multiple priorities and deliver high-quality results in a fast-paced environment.
Excellent written and verbal communication skills with the ability to explain complex concepts to diverse audiences.
Strong attention to detail and commitment to data quality and accuracy.

Nice To Haves

Experience supporting CECL, stress testing, underwriting, loss forecasting, or credit risk analytics functions.
Knowledge of dashboarding and reporting tools such as Tableau, Qlik Sense, or similar business intelligence platforms.
Experience supporting model governance, validation, audit, and regulatory review processes.
Strong understanding of financial planning and analysis processes within a banking environment.
Experience developing enterprise-scale data platforms and analytical solutions.
Proven ability to collaborate effectively across Finance, Risk, IT, Data Management, and business organizations.
Strong project leadership and stakeholder management skills.
Experience driving process automation and workflow optimization initiatives.
Familiarity with model risk management frameworks and regulatory expectations.

Responsibilities

Gather, analyze, and document FP&A business requirements and translate them into scalable analytical and technical solutions.
Design, develop, implement, and maintain robust data workflows supporting financial planning, forecasting, reporting, and credit analytics.
Lead the development, implementation, and maintenance of CECL credit loss models supporting regulatory reserving, stress testing, and underwriting activities.
Personally participate in coding, testing, deployment, and maintenance of analytical models, workflows, and production processes.
Develop deep expertise in Webster’s data platforms, systems, tools, and reporting environments.
Partner with IT, Data Management, Finance, Risk, and business stakeholders to develop data architectures, workflows, and reporting solutions.
Create intuitive reports, dashboards, and data visualizations that enable effective decision-making across the organization.
Anticipate, identify, and resolve data quality, workflow, and operational challenges impacting model and reporting processes.
Maintain comprehensive workpapers and development documentation supporting governance, audit, validation, and regulatory requirements.
Author technical documentation detailing model design, development, testing, implementation, and ongoing enhancements.
Effectively communicate analytical findings, technical concepts, and business insights to both technical and non-technical audiences.
Lead and/or participate in discussions with Executive Management, Model Risk Management, Audit, Regulatory, and cross-functional project teams.
Drive continuous improvement initiatives by identifying opportunities to automate processes and enhance analytical capabilities.