Job Description

Job Title: Insurance Data Analyst

Location: Minnesota (MN), USA

Job Type: Full-Time (Onsite/Hybrid)

Experience Level: 0–3 Years

Client: Confidential

Visa Eligibility

• Open to candidates on: OPT, CPT, H1B, H4 EAD, L2 EAD, GC,
• No C2C / No Sponsorship available at this time

Job Summary

We are seeking a detail-oriented and analytical Insurance Data Analyst to support business decision-making across underwriting, claims, and risk management functions. The ideal candidate will work with large insurance datasets, generate insights, and build reports that improve operational efficiency and customer outcomes.

Insurance analytics plays a key role in evaluating risk, pricing policies, and detecting fraud using data-driven insights .

Key Responsibilities

• Collect, clean, and validate large datasets from policy, claims, and customer systems
• Perform exploratory data analysis to identify trends, anomalies, and business insights
• Support underwriting and risk assessment by analyzing historical claims and policy data
• Develop and maintain dashboards and reports for stakeholders (claims, finance, operations)
• Identify patterns related to fraud detection, claim leakage, and customer behavior
• Write optimized SQL queries for data extraction and transformation
• Collaborate with cross-functional teams including actuaries, underwriters, and business analysts
• Perform data quality checks and ensure data integrity across systems
• Assist in predictive analysis and forecasting (claims, premiums, retention trends)
• Present insights in a clear and business-friendly manner

Required Skills & Qualifications

• Bachelor’s degree in Data Analytics, Statistics, Finance, Computer Science, or related field
• Strong knowledge of SQL for data querying and manipulation
• Proficiency in Excel (Advanced) – Pivot Tables, VLOOKUP, Macros
• Basic to intermediate knowledge of Python or R for data analysis
• Experience with data visualization tools such as Power BI / Tableau
• Understanding of insurance concepts: claims, underwriting, premiums, risk modeling
• Strong analytical thinking and problem-solving skills
• Good communication and stakeholder interaction skills

Preferred Skills

• Experience with ETL processes and data pipelines
• Familiarity with insurance systems (Policy Admin, Claims Management)
• Exposure to predictive analytics / machine learning models
• Knowledge of SAS, SPSS, or Snowflake is a plus
• Understanding of fraud analytics and risk scoring models

Key Business Areas Supported

• Claims Analytics
• Underwriting & Risk Analysis
• Customer Insights & Retention
• Fraud Detection
• Financial & Premium Analysis

Why Join?

• Opportunity to work on real-world insurance datasets and risk models
• Exposure to end-to-end analytics lifecycle (data → insights → decision-making)
• Collaborative environment with actuarial, finance, and business teams
• Strong career growth in Insurance Analytics & Data Science

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