Lead Business Analyst

About the role

The Lead Business Analyst conducts moderate-to-high complexity analysis of automated surveillance systems that detect potential violations of regulatory rules. This role is responsible for understanding, validating, enhancing, and supporting surveillance patterns across multiple asset classes and regulatory domains. The analyst serves as the bridge between regulatory requirements and the technical implementation of surveillance logic, ensuring patterns produce accurate, complete, and defensible results.

Responsibilities

• Conducts moderate-to-high complexity analysis of automated surveillance systems
• Understands, validates, enhances, and supports surveillance patterns across multiple asset classes and regulatory domains
• Serves as the bridge between regulatory requirements and the technical implementation of surveillance logic
• Ensures patterns produce accurate, complete, and defensible results
• Actively leverages generative AI tools to accelerate analysis, documentation, and automation
• Serves as the domain expert who ensures regulatory accuracy and completeness of all outputs

Requirements

• Bachelor's degree and 5+ years of experience in financial regulatory technology, surveillance systems, or capital markets data analysis
• Proficiency in SQL for large-scale data analysis on distributed platforms
• Proficiency in at least one scripting/programming language (Python) for data analysis, automation, and tool development
• Strong analytical skills with the ability to independently investigate data discrepancies and validate system outputs
• Advanced proficiency in spreadsheet tools for business and operational analysis
• Excellent documentation skills - ability to translate complex technical implementations into clear business-facing knowledge documents and Business Requirement Documents (BRDs)

Qualifications

• Major in Business Administration, Finance, Computer Science, or related field; advanced degree preferred
• Experience with project management and documentation tools and their APIs, and leading UAT efforts
• Knowledge of SEC/FINRA regulatory rules and reporting requirements
• Experience with data science efforts within financial market data (stocks, ETFs, options), and presenting findings to a wide audience
• Experience leveraging generative AI tools (LLMs, AI coding assistants) and validating AI-generated output to accelerate data analysis, code comprehension, documentation, and automate production workflows
• Strong interest in learning more about US financial market structure and evolving regulatory landscape
• Experience reverse-engineering surveillance pattern source code to build comprehensive knowledge documentation
• Familiarity with surveillance pattern architectures (exception generation, scoring, aggregation, reconciliation)
• Experience with distributed query engines and big data platforms
• Experience with source code management and release branch workflows