Analytics Team Lead - Vice President

About the Role The Technology and Risk Controls Engineering team within Morgan Stanley's Technology Organization is seeking an Analytics Team Lead-Vice President to provide hands-on data analytics expertise and technical leadership in support of continuous control monitoring. The role will identify and evaluate data sources, perform data analysis, and assess whether data is suitable to support control metrics. The role will partner with teams across the metric development lifecycle to define requirements, confirm data suitability, onboard new feeds, complete user acceptance testing (UAT), and maintain supporting documentation. This is a technical leadership role with no direct reports or formal people-management responsibilities. The team lead will own delivery of assigned data analytics and metric-development workstreams and coordinate junior analysts' work through clear expectations, deadlines, and technical guidance. The role will ensure deliverables meet documented acceptance criteria, are completed on time, and have identified errors corrected and retested before submission. The team lead will also mentor junior analysts and developers and report on workstream delivery progress. Responsibilities: • Collaborate with data subject matter experts (SMEs), control owners, and other team members to understand and document data requirements. • Independently investigate ambiguous data and metric requirements, challenge assumptions, and recommend fit-for-purpose analytical approaches with limited direction. • Identify and evaluate potential data sources. • Evaluate and document data in terms of volume, velocity, variety, veracity, and value. • Write scripts to extract, transform, and analyse data from various sources. • Assess and document whether data is suitable to support control metrics. • Translate approved Control Measurement Record requirements into documented, tested, and validated metric calculation logic; coordinate handover to platform engineering and verify implementation through UAT. • Document requirements for new data sources and enhancements to existing sources. • Partner with the database team to onboard new data feeds in accordance with Technology standards and procedures, including UAT planning, execution, and documentation • Guide the visualization team on the use of data for metric development. • Follow the company's Software Development Life Cycle (SDLC) policies. • Create and maintain documentation demonstrating adherence to required processes for review by the Second Line and Internal Audit. • Own planning and delivery of assigned data analytics and metric-development workstreams, including prioritization, capacity planning, quality assurance, dependency management, and milestone tracking. • Track workstream progress using project management tools such as JIRA, report delivery status, and promptly escalate risks and issues. • Provide day-to-day technical leadership for junior analysts by coordinating task assignments, clarifying requirements and acceptance criteria, setting delivery deadlines, and monitoring work through completion. • Review junior analysts' analyses, SQL queries, scripts, testing evidence, and documentation for accuracy, completeness, and adherence to requirements and standards before submission. • Apply quality assurance checks, including data reconciliation, validation, and peer review; ensure identified errors are corrected and retested before delivery. • Mentor junior analysts and developers through hands-on coaching, code reviews, knowledge sharing, and guidance on analytical methods, coding standards, testing, and documentation Requirements: • At least 5 years of experience writing Python scripts for data analysis, including extensive knowledge of pandas, regular expressions (re), lambda functions, and NumPy. • Advanced SQL skills, including developing and reviewing complex queries and validating metric calculation logic • Experience developing code using AI-assisted tools such as Claude, OpenAI tools, and GitHub Copilot. • Experience applying AI agents to automate work processes. • At least 5 years of demonstrated data analysis experience. • At least 5 years of experience working with database and reporting teams. The five-year experience requirements may be met concurrently; they do not require separate periods of employment. • Experience providing technical leadership for data analytics workstreams and coordinating junior analysts' work, with accountability for priorities, capacity planning, deadlines, quality, and accurate, timely delivery. • Ability to exercise independent analytical judgment, resolve ambiguous requirements, challenge assumptions, and recommend appropriate approaches with limited direction. • Experience translating approved metric requirements into calculation logic, validating results, and supporting engineering handover and UAT. • Experience reviewing analyses, SQL queries, scripts, and supporting documentation, with strong attention to detail and a structured approach to identifying and resolving errors. • Ability to mentor junior analysts and developers, explain technical concepts clearly, and provide constructive technical guidance. • Strong understanding of technology controls and technology risks. • Intermediate Excel skills, including string manipulation functions, VLOOKUP, and PivotTables. • Strong communication and organizational skills. • Project management experience. Preferred: • Knowledge of DevOps tools and concepts. • Experience with GitHub and code deployment. • Adaptability to new technologies and changing requirements. • Ability to manage competing priorities in a dynamic, fast-paced environment. • Experience with Snowflake. WHAT YOU CAN EXPECT FROM MORGAN STANLEY: At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years. Our values - putting clients first, doing the right