Data Analyst

Role & responsibilities: 1. Perform efficient and accurate manual data extraction from various document formats using advanced Microsoft Excel skills. This includes leveraging complex formulas, data validation, and efficient navigation techniques to expedite the extraction process. 2. Analyze project data to identify trends, patterns, and insights. 3. Develop and maintain data queries and reports using SQL (preferred). 4. Automate data processing tasks using Python scripting where applicable (advantageous). 5. Organize and maintain project-related data and documentation effectively. 6. Identify and troubleshoot technical issues, escalating them as needed. 7. Assist in optimizing internal processes and workflows. 8. Collaborate with team members to meet project objectives. 9. Potentially support the administration and use of eDiscovery platforms like Relativity (a plus). Requirements: 1. Proven working experience as a Data Analyst or Business Data Analyst. 2. Technical expertise regarding data models, database design development, data mining. 3. Advanced proficiency in Microsoft Excel, particularly for efficient manual data extraction. 4. Keen attention to detail with a strong commitment to accuracy. 5. Excellent organizational and time-management skills. 6. Ability to work both independently and collaboratively in a team setting. 7. Strong analytical and problem-solving capabilities. 8. Clear and concise communication skills for presenting technical findings. Essential Skills: 1. Expertise in Microsoft Excel, including advanced formulas (e.g., VLOOKUP, INDEX/MATCH, SUMIFS), data validation, pivot tables, and keyboard shortcuts for rapid data extraction. 2. Strong analytical and logical thinking abilities. 3. Exceptional written and verbal communication skills. 4. Ability to quickly adapt to and learn new software and technologies. Beneficial Skills: 1. Experience with SQL for querying and managing databases. 2. Familiarity with Python for scripting and data automation. 3. Experience in the Data Breach/Incident Response domain, including search strategies and data management (a plus). 4. Exposure to other data visualization tools. 5. Understanding of data warehousing concepts.