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Tristar Insurance Services LLC

Data Analyst I

Tristar Insurance Services LLC, Signal Hill, California, United States

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Job Details

Level Entry

Job Location Signal Hill Office - Signal Hill, CA

Remote Type Fully Remote

Position Type Full Time

Education Level High School Diploma or GED

Salary Range $114000.00 - $140000.00 Salary/year

Travel Percentage Negligible

Job Shift Day

Job Category Information Technology

Data Analyst I

Assist in building data warehouse, dashboards, and reporting tools for actuarial, claims, and underwriting teams. Collaborate with business units to develop data-driven insights for loss prevention and reserve modeling. Clean, organize, and merge structured data from internal and third-party sources. Write queries and scripts using SQL and Python or R to extract and analyze data efficiently. Ensure data integrity and accuracy in reports and data feeds used for compliance, audit, and strategic planning. Analyze claims, policy, and exposure data to identify trends in injury types, loss costs, and claim durations. Apply basic statistical techniques or predictive models to support pricing, claims triage, or fraud detection. PREFERRED SKILLS (Not Required)

Knowledge of workers' compensation insurance and claims workflows Internship or project experience in insurance analytics, risk modeling, or predictive modeling. Understanding of regulatory reporting and industry data sources (e.g., NCCI, ISO). Qualifications

QUALIFICATIONS REQUIRED:

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or related field. 0-3 years of experience in data science, analytics, or insurance-related projects (academic or professional). Familiarity with data tools such as SQL, Python, R, or SAS. Familiarity with Data warehouse techniques and practices Hands on any data warehouse product Exposure to data visualization tools (e.g., Power BI, Tableau). Strong attention to detail, curiosity, and willingness to learn industry-specific data concepts. Ability to work independently and collaboratively with cross-functional teams.