Lead Statistician, Wage & Hour Analytics

Jackson Lewis P.C.; City of White Plains (NY); On-site; USD 125,000 - 150,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k)

Health savings account

Holidays, vacation, and sick time

Employee assistance program

Job summary

Jackson Lewis P.C. in New York seeks a Lead Statistician for the Wage & Hour Data Analytics group to manage complex analytics on class/collective actions and DOL audits. You will oversee 2-3 statisticians, ensuring timely, quality work and clear communication to attorneys and clients.

The role requires seven years of wage-hour data experience, plus strong R/Python and Excel skills, and the ability to translate findings for non-technical stakeholders in a legal context.

Qualifications

• Master’s degree in applied statistics, mathematics, econometrics or equivalent.
• Seven years of data experience with Wage & Hour topics and payroll data.
• Experience leading analytics projects and managing teams.
• Able to communicate technical results to counsel and stakeholders.

Responsibilities

• Lead client and attorney strategies on class and collective action data analytics.
• Oversee 2–3 statisticians, ensuring on-time, high-quality work.
• Explain analysis methods and results clearly to attorneys and clients.
• Expand data tools and automate processes within the W&H analytics team.

Skills

Data analytics

R

Python

Team leadership

Project management

Stakeholder communication

Quality control

Education

Master's degree in statistics

Tools

Excel

Job description

Jackson Lewis P.C. in New York seeks a Lead Statistician for the Wage & Hour Data Analytics group to manage complex analytics on class/collective actions and DOL audits. You will oversee 2-3 statisticians, ensuring timely, quality work and clear communication to attorneys and clients.

The role requires seven years of wage-hour data experience, plus strong R/Python and Excel skills, and the ability to translate findings for non-technical stakeholders in a legal context.