Lead Data Analyst

Grade Level (for internal use): 08 Role Scope: This team delivers and maintains accurate, complete, and timely financial datasets for Compustat Fundamentals, covering public companies from North America region. Operating with advanced research methodologies and cutting-edge tools, our team provides essential intelligence that empowers clients across various sectors to make informed financial decisions. We value operational excellence, continuous learning, and collaborative problem-solving in our mission to deliver the highest quality financial data. What You’ll Do (Key Responsibilities): Lead complex data collection, extraction, and advanced cleansing for Compustat Fundamentals datasets while mentoring junior team members on best practices and quality standards Design and optimize SOPs for data sourcing, tagging, and loading processes while implementing advanced metadata frameworks and quality control mechanisms Perform comprehensive data validation and reconciliation across multiple data sources, identifying patterns and developing enhanced business rules for improved accuracy Own end-to-end data integrity for assigned North America region datasets, managing stakeholder relationships and ensuring seamless data delivery workflows Analyze and resolve complex exceptions and anomalies independently, providing technical guidance to team members and implementing systematic solutions Drive process improvement and automation initiatives by leveraging advanced tools including Python and AI/LLM technologies to enhance research efficiency and data quality How Impact Will Be Measured (Success Metrics): • Dataset quality KPIs (accuracy, completeness, consistency); reduced exceptions and cycle time • Timely resolution of client/vendor issues; improved satisfaction • Quality/maintainability of rule books and SOPs (audit outcomes; update cadence) • Measurable efficiency and quality gains from UAT, automation, and process improvement For This Role You'll Need to Have (Skills & Competencies): Technical Skills: Experience with AI/LLM tools and frameworks such as OpenAI APIs, Hugging Face, or LangChain for automating financial document analysis and data extraction Knowledge of cloud platforms such as AWS, Azure, or Google Cloud for data processing, storage, and advanced analytics implementation Familiarity with data visualization tools such as Tableau, Power BI, or Python libraries including matplotlib and seaborn for reporting and insights generation Experience in leading cross-functional projects and implementing automation solutions that enhance operational efficiency and reduce manual processing time Functional & Behavioural Skills: Advanced understanding of financial statements, US GAAP reporting standards, and their application in data standardization and validation processes Strong proficiency in database management tools such as SQL, MySQL, or PostgreSQL for complex querying, data modeling, and optimization techniques Experience with programming languages such as Python, R, or similar for data manipulation, automation, and analytical workflows Proven ability to lead process improvements, mentor junior staff, and manage multiple datasets while maintaining high quality standards Preferred Education & Experience: Bachelor's degree in Finance, Commerce, Economics, Accounting, or related field from an accredited institution; Master's degree preferred 2-5 years of experience in financial data operations, research, or analytical roles with demonstrated progression in responsibilities Key Interfaces & Stakeholders: • Associates and Specialists within Data Research & Operations. • Data Stewards, Data Automation & Transformation, and Data Quality teams. • Technology team which is responsible for platforms, tools, and pipelines. • External vendors and, where applicable, clients via support channels.   What’s In It For You?

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