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 provides strategic and delivery leadership for practical, scalable AI solutions that address real finance challenges end to end—from problem framing and solution design through deployment, change management, and adoption. The role partners closely with senior Finance leadership to align priorities, deliver solutions, and ensure measurable outcomes. This position provides an excellent opportunity to interact with different business areas across State Street.
Who we are looking for
The ideal candidate combines strong analytical thinking with business acumen and play a hands-on leadership role in the delivery of AI capabilities, agentic approaches, and low‑code/no‑code solutions to deliver integrated, optimized solutions. Success in this role requires the ability to influence and align senior stakeholders, translate complex technical concepts into clear business decisions, and drive delivery through cross‑functional project teams. This leader connects technology choices to tangible Finance outcomes—improving insight quality, controls, efficiency, and decision‑making—and establishes KPIs, measurement approaches, and governance to sustain results.
What you will be responsible for:
Build Agentic AI & Copilot Solutions for Finance
- Lead cross‑functional delivery teams to design and deliver agent‑based workflows that can plan, reason, and execute tasks across finance processes (with appropriate human oversight, controls, and governance).
- Own solution strategy for LLM copilots supporting 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; define quality controls and KPI monitoring to sustain performance over time
- Prompt Engineering & Context Design (Finance‑Grade)
- Set standards for finance‑grade prompting and context (e.g., P&L, cost centers, accounting rules, materiality thresholds) and structure outputs for decision‑making, auditability
- Establish reusable prompt patterns, evaluation approaches, and guardrails to reduce hallucinations, increase consistency, and meet governance expectations
Apply Data Science Where It Matters
- Apply analytics and data science methods (e.g., anomaly detection, classification, forecasting support, explainability) where they most improve finance efficiency, 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
- Lead delivery using no‑code and low‑code tools to accelerate time‑to‑value while maintaining controls and quality standards, including:
- 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, align priorities, and lead solution design that fits how work actually gets done
- Lead project planning and execution (scope, timeline, dependencies, risks), support rollout and adoption through documentation and training, and iterate based on user feedback
Responsible AI & Controls‑Aware Delivery
- Ensure solutions are explainable, auditable, and aligned with governance expectations
- Provide clear status, risk, and outcomes reporting to senior management
- Validate AI outputs against financial data and business logic; implement monitoring, KPI dashboards, and a continuous improvement cadence to maintain quality and value over time
Skills and experience needed:
- Bachelor’s degree in AI, Data Analytics, Computer Science, Engineering, or a related field
- 8+ years of experience in AI technologies, data science, analytics, and automation with demonstrated leadership of programs/teams (financial services preferred)
- Strong analytical and problem‑solving skills
- Experience working with large, complex datasets
- Proficiency in SQL and Python
- Experience with data warehousing, data modelling, ETL design
- Understanding of Finance, Risk and/or Treasury business processes
- Experience with data visualization tools (e.g., Power BI, Tableau)
- Experience with automation tools (e.g., low-code platforms, RPA, workflow tools)
- Demonstrated ability to lead cross‑functional project teams, manage delivery plans, and drive adoption through change management
- Knowledge of data governance, data quality, and regulatory compliance concepts (e.g., BCBS 239 principles)
- Strong written and verbal communication skill