Data Analytics & Management, AVP

About the job

The Finance Data and AI Office (DART) delivers trusted data, analytics, and AI-enabled solutions across Finance, Risk, and Treasury. This role sits within the Automation, Analytics & AI pillar and focuses on building practical, scalable AI solutions that address finance challenges end to end—from problem framing and solution design through deployment and adoption.

The ideal candidate combines strong analytical thinking with business curiosity and judgment and can thoughtfully apply the right mix of AI capabilities, agentic approaches, and low-code/no-code tools to design integrated, optimized solutions. Success in this role requires the ability to connect technology choices to tangible Finance outcomes—improving insight quality, controls, efficiency, and decision-making.

• Build Agentic AI & Copilot Solutions for Finance
  • Design and deliver agent-based workflows that can plan, reason, and execute tasks across finance processes (with appropriate human oversight and controls).
  • Implement solutions that use LLM copilots for finance narratives, variance explanations, exception triage, and root-cause analysis
  • Combine AI reasoning with deterministic logic (rules, thresholds, accounting constraints, materiality) to ensure reliability in controlled environments
• Prompt Engineering & Context Design (Finance-Grade)
  • Create and refine prompts grounded in finance context (e.g., P&L, cost centers, accounting rules, materiality thresholds) and structure outputs for decision-making
  • Build reusable prompt patterns, evaluation approaches, and guardrails to reduce hallucinations and increase consistency
• Apply Data Science Where It Matters
  • Use analytics and data science methods (e.g., anomaly detection, classification, forecasting support, explainability) to strengthen finance insight and controls
  • Analyze large, complex datasets to identify breaks, drivers, trends, and actionable signals relevant to Finance operations and reporting
• Enable AI Using No-Code / Low-Code Platforms
  • Use no-code and low-code tools (e.g., Alteryx, Power BI, Power Platform or similar) to
  • Operationalize AI outputs into finance workflows
  • Orchestrate AI-driven steps alongside rules-based logic
  • Surface AI-generated insights, exceptions, and narratives to end users
  • Know when low-code is sufficient and when custom logic or data science is required
• Embed Solutions into Finance Workflows
  • Partner with Finance, Risk, and Treasury teams to understand processes end-to-end and design solutions that fit how work actually gets done
  • Support rollout and adoption through documentation, training, and iteration based on user feedback
• Responsible AI & Controls-Aware Delivery
  • Ensure solutions are explainable, auditable, and aligned with governance expectations
  • Validate AI outputs against financial data and business logic; design monitoring to maintain quality over time

• Bachelor’s degree in AI, Data Analytics, Computer Science, Engineering, or a related field
• 5-7 years of experience in emerging AI technologies, data science, analytics, automation (financial services preferred)
• Strong analytical and problem-solving skills
• Experience working with large, complex datasets
• Proficiency in SQL and Python
• Knowledge of data warehousing, data modelling, ETL design
• Experience with data visualization tools (e.g., Power BI, Tableau, or similar)
• Exposure to automation tools (e.g., low-code platforms, RPA, workflow tools)
• Understanding of Finance, Risk and/or Treasury business processes
• Strong written and verbal communication skills

• Microsoft Co-pilot Studio
• Microsoft 365 Co-pilot
• Databricks
• Anthropic/Claude
• Power BI/Tableau
• Alteryx
• Microsoft Fabric
• Microsoft Power App
• Microsoft Power Automate

State Street is an equal opportunity and affirmative action employer. We welcome candidates from diverse backgrounds and experiences.

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