Data Analyst

Data Analyst

Anello Data Solutions LLC

Overview

Anello Data Solutions is seeking a Data Analyst with expertise in wage and hour class action damages calculations. This role involves analyzing large payroll and timekeeping datasets, developing damage models, and supporting litigation strategies through clear, data-driven insights. The ideal candidate will be highly proficient in R/R Studio, Excel, and Power Query and comfortable working with structured payroll and HR data. Experience with PDF conversion and data cleaning is also essential.

Expectations
• 30-50 hours per week, depending on project needs.
• Ability to manage multiple projects and deliver accurate, timely results.
• Regularly and clearly communicate results and issues.

Responsibilities
• Analyze and interpret large wage and hour datasets to quantify potential damages.
• Develop structured, reproducible workflows in R/R Studio for wage calculations, statistical sampling, and damages estimation.
• Utilize Excel and Power Query to process payroll, timekeeping, and HR data from multiple sources.
• Perform data cleaning and standardization, ensuring accuracy and consistency across datasets.
• Extract and convert data from PDFs into structured formats for analysis.
• Identify trends, discrepancies, and patterns in pay and time records.
• Create clear, well-documented reports and visualizations to communicate findings effectively.
• Collaborate with attorneys, expert witnesses, and consultants to refine analyses and provide strategic insights.

Qualifications
• Bachelor’s or Master’s degree in Statistics, Applied Mathematics, Economics, or a related field AND/OR 1-2 years of experience in data analysis, economic consulting, or a related field.
• Proficiency in R/R Studio (required) for data manipulation, modeling, and reproducible analysis.
• Strong skills in Excel and Power Query (both required) for processing and transforming structured datasets.
• Experience with data cleaning and PDF conversion is highly preferred.
• Experience working with large payroll and timekeeping datasets is a plus.
• Experience in any coding language is a plus.