Data Analytics & Management - Officer

State Street•Boston, MA

8d•Onsite

About The Position

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 solutions that address real finance challenges end to end—from problem framing and solution design through deployment and adoption—including data governance and internal control capabilities that align to regulatory expectations and standards.

Requirements

Bachelor’s degree in AI, Data Analytics, Computer Science, Engineering, or a related field.
3-5 years of experience in emerging AI technologies, data science, analytics, automation (financial services preferred)
Strong analytical and problem-solving skills
Proficiency in SQL and Python
Familiar with data warehousing, data modelling, ETL concepts
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

Nice To Haves

Knowledge of Microsoft Co-pilot Studio
Knowledge of Microsoft 365 Co-pilot
Knowledge of Databricks
Knowledge of Anthropic / Claude
Knowledge of Alteryx
Knowledge of Microsoft Fabric

Responsibilities

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, and surface AI-generated insights, exceptions, and narratives to end users.
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.
Regulatory Alignment, Data Governance & Controls: Contribute to BCBS 239 and broader regulatory aligned outcomes by improving traceability, accuracy, completeness, timeliness, and evidencing for critical finance/risk data used in aggregation and reporting. Ensure solutions delivered are consistent with broader regulatory expectations and embed appropriate data governance and controls from design through production.

Benefits

retirement savings plan (401K) with company match
insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages
paid-time off including vacation, sick leave, short term disability, and family care responsibilities
access to our Employee Assistance Program
incentive compensation including eligibility for annual performance-based awards
eligibility for certain tax advantaged savings plans
inclusive development opportunities
flexible work-life support
paid volunteer days
vibrant employee networks