Act as an individual contributor, providing project oversight and guidance to Decision Scientists, and supporting the Decision Science Manager in executing against the objectives of assigned business group. Using an interdisciplinary approach of leveraging concepts from business, applied statistics and math, operations research, information technology, process design and behavioral sciences, the incumbent will engage in consultative partnerships, aligning with the Line of Business (LOB) to produce analytic insights that help the business make informed, data-driven decisions with an objective of driving quantifiable, optimized business results in support of company goals.
Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.
Lead Business Data Architecture Strategy
- Define current-to-target state data architecture blueprints supporting CSBB business capabilities, aligning to enterprise standards and AI readiness objectives
- Establish domain-based data models, ownership structures, and cross-domain data flow designs to eliminate silos and improve interoperability
- Lead the development, maintenance, and socialization of target-state architecture blueprints, data domain models & ownership maps, cross-domain lineage / flow diagrams, architecture standards & design patterns
Drive Data Product Alignment & Rationalization
- Partner with Business Data Product teams to ensure consistent architecture alignment across data products and reporting assets
- Lead rationalization of legacy BI/reporting ecosystem, enabling consolidation and migration to scalable, modern platforms aligned to product strategy
Enable AI-Ready Data Foundations
- Define and enforce architectural standards that ensure data quality, lineage, certification, and governance are embedded in design-time workflows
- Support the development of AI-ready data assets and enable scalable analytics and automation capabilities across CSBB
Portfolio Alignment & Intake Governance
- Collaborate with portfolio strategy functions to ensure intake, prioritization, and solution design align with architectural principles and business value drivers
- Provide architectural oversight to ensure new initiatives align with long-term target state and do not introduce fragmentation
Stakeholder Partnership & Strategic Alignment
- Serve as a key interface between business stakeholders, enterprise architects, platform teams, and data delivery managers
- Influence senior leadership through clear articulation of architecture strategy, trade-offs, and value realization
Enable Federated Analytics & Cloud Migration
- Foster communication and partnership across multiple levels of the organization including engagement with LOB leaders and senior managers. Responsible for stewarding relationships, delivering on promises, and building trust with partners while delivering on LOB and company goals.
- Mentor, guide, and act as a force multiplier in support of analytics practitioners across CSBB in aligning data & reporting assets with broader enterprise data transformation objectives and target state architecture strategy, including cloud migration efforts
- Promote consistent data structures, access patterns, and governance practices to enable scalable and efficient delivery
Value Realization & Transformation Enablement
- Define and track success metrics (e.g., reduced redundancy, improved time-to-insight, adoption of standardized assets)
- Support change management, communication strategies, and adoption efforts for new data architecture and product capabilities
- Represent the CSBB Data & Governance group in various forums, work streams, and senior leadership reviews. Cultivate relationships with partner federated and hub analytics teams to drive efficient decision science delivery against shared objectives.
- Pursue business outcomes valued through increased revenue and/or efficiency leveraging data-driven insights powered by analytics in support of enhanced decision-making. Focus on continuous improvement in decision science delivery and outcomes in pursuit of business optimization.
Promote Best Practices & Continuous Improvement
- Champion architectural rigor, standardization, and reuse across all CSBB data initiatives
- Foster a culture of proactive design vs. reactive solutioning aligned to product-based delivery principles
- Champion the use of cloud tools to solve business challenges and deliver solutions that are timely, accurate, and adherent to change management & governance standards.
- Exercise sound judgment, risk management, and foster a client centric culture throughout design, development, and deployment practices.
QUALIFICATIONSRequired QualificationsThe requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- The incumbent must demonstrate a combination of academic aptitude, quantitative skills, business acumen, working knowledge of Finance & Banking concepts, enterprise data management systems, strategic and creative thinking, and excellent written and verbal communications skills
- Bachelor's degree in Banking, Finance, Economics, Data Science, Computer Science, Engineering, Analytics, Mathematics, or related field; or equivalent experience
- 7+ years of experience in data architecture, data engineering, decision science, or analytics within banking or financial services
- Demonstrated experience designing business data models, data architectures, and scalable data solutions across enterprise environments
- Strong understanding of modern data platforms (e.g., cloud data warehouses, distributed processing frameworks) and data product concepts
- Proven ability to influence cross-functional stakeholders and align business and technology priorities
- Must act as role model, able to perform in a cross-functional and collaborative team environment focused on supporting business partners with enhanced insights
- Demonstrated ability to engage and manage a diverse set of internal business partners, product sets, and projects, connecting insights with execution and business impact
- Innovative and strategic thinker with ability to connect to practical application, providing leadership on target initiatives, with a strong bias to action and focus on quantifiable business impact
- Experience in managing multiple projects with tight deadlines in a collaborative environment, with ability to pivot and align resources to drive maximum impact
- Ability to maintain a high level of competency in statistical and analytical principles, tools, and techniques. Champion application of emerging decision science techniques by supporting teammate training and development and building business partner awareness
- Incumbent should have an understanding of various database environments (IBM DB2, Oracle), technical programming skills (SAS, SQL, Toad), exposure to applied data science tools (R, Python, SAS Viya), comfortability with cloud computing platforms (e.g. Snowflake, Amazon S3, Microsoft Azure) familiarity with data visualization and BI tools (Tableau, Power BI, Qlik Sense), and demonstrated proficiency in Microsoft Office Suite (SharePoint, Excel, PowerPoint, Word)
- Experience leading complex, multi-domain initiatives with measurable business impact
- Strong communication, storytelling, and executive presentation skills
Preferred Qualifications- Master's or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
- 10+ years of experience in Banking, Finance, Decision/Data Science, Analytics, Computer Science, Applied Mathematics or Engineering
- 2+ years of analytics management experience with a diverse project focus and demonstrated results
- Experience supporting large-scale cloud migrations and modernization initiatives
- Familiarity with AI/ML data requirements and operationalization frameworks
- Experience in BI rationalization, data product lifecycle management, or enterprise data governance alignment
