Manager, Financial Analytics

Webster Bank•White Plains, CT

3d•Hybrid

About The Position

The Financial Analytics Manager is responsible for the quarterly execution of the vendor models. This includes the preparation of CECL loan data across each of the relevant portfolios, coordination with data, credit, business line, and operations teams on any issues, and presenting the results to the CECL Committee and external auditors at least quarterly. The role plays a key role in bridging business objectives with data-driven insights at Webster. This position is responsible for understanding and translating complex business requirements into analytical solutions, leveraging Webster’s data systems and tools, designing, coding, and maintaining data workflows. The role involves overseeing the integration and processing of both structured and unstructured data sources to enhance data usability. The individual needs to collaborate with IT, Data Team, and LoB partners in developing data workflows, data analysis, and reporting. The Manager Financial Analytics role designs and supports statistical and predictive models that inform strategic decision-making. This role is right for you if you’re a “hands-on” coder and analyst, take ownership and sound business understanding.

Requirements

3 + years of industry experience in Data Analytics, Data Science, Data Engineering, Software Development or related field.
Experience working with complex data structures within a RDMS (Oracle, SQL).
Proficient in Python /SAS Programming Language.
Knowledge of advanced statistical techniques and concepts and experience with applications.
Experience in building, validating and deploying statistical or predictive models.
Strong business knowledge and familiarity with financial data systems and architecture.
Ability to interpret and translate business needs into analytical frameworks.
Strong analytical and problem-solving skills and ability to work in a collaborative team environment.
Excellent communication skills to convey complex technical concepts to non-technical stakeholders.
Ingenuity, analytical thinking, resourceful, persistent, pragmatic, motivated and socially intelligent.
Technically oriented, proactive, and enthusiastic, with good attention to details.
Proven ability to manage multiple priorities, meet deadlines, and adapt to changing business needs in a fast-paced environment.

Nice To Haves

5+ years of industry experience in Data Analytics, Data Science, Data Engineering, Software Development or related field.
Experience working with unstructured data using advanced OCR and NLP techniques.
Experience with one or more cloud-based computing platforms: AWS, Azure, GCP.
Experience in designing efficient and robust data workflows (e.g.- Apache Airflow).
Experience in integrating automated unit test cases and code scanning tools with CI/CD pipeline (E.g. – GitLab).
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.

Responsibilities

Develop expert knowledge and experience with Webster’s data systems and tools.
Develop strong relationships with Webster lines of business, Finance, Credit, Data, Risk & IT partners to ensure consistency and appropriateness of the team’s various processes and impact on FA models. This includes changes to external systems, changes in database content and structure, and changes in applied methodology.
Execute and support Dual Risk Rating model building, monitoring and model refresh.
Analyze and organize large structured and unstructured data to derive actionable insights and support decision-making processes.
Assist FA team and collaborate internally.
Document and communicate changes to data structure, content and logic that has impact on models.
Assist in the coding and testing of changes to existing models.
Collaborate with cross-functional teams to understand data requirements, business objectives and implement effective solutions.
Work with external data sources, APIs.