Business/Data Analyst (SQL+ Python & Model Risk)

Position Title : Business/Data Analyst (SQL+ Python & Model Risk)

Location : New York, NY (Onsite/Hybrid)

Experience : 8+ Years

Employee Type : Full Time with Benefits

Job Description

We are seeking a highly skilled Business/Data Analyst with deep hands‑on experience in SQL, Python, and a strong understanding of Model Risk Management (MRM) practices. The ideal candidate will support the design, analysis, and enhancement of model governance workflows, data pipelines, reporting frameworks, and lifecycle controls across the enterprise.

This role combines domain expertise, analytical rigor, and technical fluency to drive insights, improve governance processes, and empower model risk, data science, and engineering teams.

Required Skills Qualifications

• Expert-level SQL (complex joins, CTEs, window functions, performance optimization).
• Strong Python skills for data analysis, automation, and workflow support (pandas, numpy, data validation scripts).
• Experience working with APIs, data models, metadata, and system integrations.
• Ability to analyze large datasets and translate findings into actionable recommendations.
• Deep knowledge of Model Risk Management (MRM) including:
• Model lifecycle processes (development → validation → approval → monitoring → retirement).
• Model governance standards and regulatory expectations (SR 11‑7, OCC 11‑12, etc.).
• Controls, documentation, testing, monitoring, and issue management.
• Experience as a Business Analyst or Data Analyst in financial services, risk, or analytics teams.
• Strong capability in requirements gathering, writing functional specifications, BRDs, user stories, and acceptance criteria.
• Ability to convert ambiguous business needs into structured, data‑driven analytical tasks.
• Excellent cross‑functional collaboration with risk, model development, validation, technology, operations, and data teams.
• Strong communication skills with the ability to simplify complex technical and regulatory concepts.

Key Responsibilities

• Support the design and enhancement of model governance workflows and lifecycle processes.
• Work with stakeholders to convert regulatory guidance and model governance needs into clear business and functional requirements.
• Perform data analysis using SQL and Python to support governance metrics, validation workflows, monitoring logic, and inventory management.
• Analyze complex model documentation, validation results, and control processes to identify gaps and improvement areas.
• Partner with engineering teams to define data models, schemas, and integration requirements.
• Create BRDs, user stories, logic specifications, calculation rules, and acceptance criteria.
• Support UAT planning and execution, including test case creation, validation, and defect tracking.
• Ensure all data flows, model processes, and governance activities comply with MRM standards and controls.
• Contribute to enhancements of reporting frameworks, dashboards, and automation scripts.
• Stay informed about evolving regulatory expectations in model risk

Good to Have

• Experience with model inventory or model governance platforms.
• Familiarity with AI workflows, RAG architectures, vector databases, and LLM‑driven automation.
• Understanding of AI governance, model explainability, and interpretability frameworks.
• Experience with workflow orchestration or AI orchestration tools (e.g., LangChain, Semantic Kernel).