Data Analytics & Management - Officer

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 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.

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.

The ideal candidate combines strong analytical thinking with business curiosity and judgment and can thoughtfully apply emerging AI capabilities and low‑code/no‑code tools to build data solutions with 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

• 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.

• 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.

• 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

• 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.

• 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

• 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…