Data-Driven Operations Analyst

DM Law; Kansas City (MO); On-site; USD 55,000 - 85,000; Full time

Job summary

DM Injury Law is seeking an Operations Support Analyst to turn data into actionable insights across intake and client services. You’ll build dashboards, own recurring reports, and support process improvements while collaborating with senior data analysts and operations teams.

The role blends analytics with QA and system support, requiring curiosity, cross-system fluency, and a willingness to leverage AI tools to speed up workflows.

Qualifications

• 1–3 years of experience in a business/analytics/operations role, legal or call-center intake is a plus.
• Ability to break down business questions, identify data needs, and present findings clearly.
• Hands-on experience building dashboards or reports (Domo preferred; Tableau/Power BI acceptable).
• Strong Excel/Google Sheets skills including formulas and pivot tables.
• Basic SQL familiarity; comfortable learning new data concepts.

Responsibilities

• Build and maintain a dashboard tracking intake performance for leadership visibility and surface trends.
• Own recurring reporting deliverables, including a weekly IT issue tracker and daily data feed for dashboards.
• Create and maintain an internal dashboard used for firm-wide communications and recognition with a lightweight admin tool.
• Produce ad hoc reports translating business questions into actionable analysis.
• Identify patterns in intake and performance data and present insights to leadership.

Skills

Dashboarding

Data analysis

Excel / Sheets

SQL basics

Communication

Education

Bachelor's degree in business, analytics, finance, or related field

Tools

Domo

Neos

Lead Docket

RingCentral

Case Status

Job description

DM Injury Law is seeking an Operations Support Analyst to turn data into actionable insights across intake and client services. You’ll build dashboards, own recurring reports, and support process improvements while collaborating with senior data analysts and operations teams.

The role blends analytics with QA and system support, requiring curiosity, cross-system fluency, and a willingness to leverage AI tools to speed up workflows.