Senior Data Analyst

Job Summary

We are seeking a detail-oriented Senior Data Analyst to join our Data Breach Response team. You will be responsible for analysing complex, often unstructured datasets resulting from cyber security incidents. Your primary goal is to identify impacted individuals, extract sensitive information (PII/PHI), and ensure data integrity for regulatory notification purposes.

Key Responsibilities

• Data Mining & Extraction: Perform manual and automated extraction of sensitive data from compromised file systems, emails, and databases.
• Data Normalization & Cleanup: Clean, de-duplicate, and format massive sets of messy data to create a "Single Version of Truth" for legal review.
• Quality Assurance: Conduct rigorous QA checks on datasets to ensure 100% accuracy before notification lists are generated.
• Reporting: Translate complex data findings into actionable reports for legal counsel and stakeholders.
• Process Optimization: Develop and maintain workflows (using Excel/SQL) to speed up the identification of PII/PHI.

Required Technical Skills

• Advanced Excel: Mastery of Pivot Tables, VLOOKUP/XLOOKUP, Index/Match, Power Query, and complex nested formulas.
• SQL: Ability to write complex queries to extract, filter, and join data from relational databases.
• Data Handling: Proven experience in Manual Extraction and Data Cleanups from unstructured sources (e.g., OCR outputs).
• Field Expertise: Minimum of 3 years specifically within the Data Breach sector.

Preferred Skills (The "Plus" List)

• VBA/Macros: Ability to automate repetitive Excel tasks to improve turnaround time.
• Python: Experience using Pandas/NumPy for large-scale data manipulation and cleaning.
• RegEx: Knowledge of Regular Expressions for pattern matching (e.g., finding SSNs or Credit Card numbers).

Professional Competencies

• High Attention to Detail: You must have a "detective" mindset to spot errors in thousands of rows of data.
• Time Management: Ability to work under tight regulatory deadlines (GDPR, CCPA, HIPAA).
• Confidentiality: A deep understanding of data privacy ethics and the sensitivity of the information being handled.

Education

• Bachelors degree in Data Science, Computer Science, Statistics, or a related field.