

Torque Technologies LLC
Data Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Technical Data Analyst in Warren, NJ (Hybrid) with a long-term contract. Requires a Bachelor’s degree and 5-7 years in P&C insurance. Key skills include SQL, Python, data analysis, and Agile experience.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
May 8, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
Warren, NJ
-
🧠 - Skills detailed
#Business Analysis #Agile #BI (Business Intelligence) #Jira #Storytelling #"ETL (Extract #Transform #Load)" #Data Architecture #Programming #Data Profiling #Mathematics #Data Accuracy #R #Data Quality #Computer Science #SQL (Structured Query Language) #Statistics #Data Analysis #Python
Role description
Position: Technical Data Analyst
Location: Warren, NJ (Hybrid)
Long Term
Qualifications:
• Bachelor’s degree in finance, Statistics, Mathematics, Computer Science, MIS, or a related field
• 5-7 years of experience as a Data Analyst or similar role in the P&C insurance industry
• Solid knowledge of the P&C insurance domain particularly policy & claims management systems
• Proven experience in data analysis, business intelligence, or related roles.
• Proficiency in data analysis tools and programming languages (e.g., SQL, Python, R, etc.).
• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication and presentation abilities.
• Ability to work independently and collaboratively in a fast-paced environment.
• Strong communication and storytelling skills to present insights to senior stakeholders
• A collaborative mindset and the ability to build alignment across teams
• Experience with Agile methodologies and tools (e.g., Jira, Confluence).
Key Responsibilities:
• Review & document current data assets across source systems
• Document the current process and limitations of the current process
• Perform exploratory data analysis to uncover trends, patterns, and anomalies
• Generate the artifacts to showcase mapping and global transformation rules that needs to be applied to the data
• Work closely with data architects and business analysts to understand the global data reporting requirements and standards
• Validate data accuracy, completeness and integrity of the data in the source systems
• Identify and document data quality issues and discrepancies
• Provide decision-support through ad-hoc analysis, data profiling etc
Position: Technical Data Analyst
Location: Warren, NJ (Hybrid)
Long Term
Qualifications:
• Bachelor’s degree in finance, Statistics, Mathematics, Computer Science, MIS, or a related field
• 5-7 years of experience as a Data Analyst or similar role in the P&C insurance industry
• Solid knowledge of the P&C insurance domain particularly policy & claims management systems
• Proven experience in data analysis, business intelligence, or related roles.
• Proficiency in data analysis tools and programming languages (e.g., SQL, Python, R, etc.).
• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication and presentation abilities.
• Ability to work independently and collaboratively in a fast-paced environment.
• Strong communication and storytelling skills to present insights to senior stakeholders
• A collaborative mindset and the ability to build alignment across teams
• Experience with Agile methodologies and tools (e.g., Jira, Confluence).
Key Responsibilities:
• Review & document current data assets across source systems
• Document the current process and limitations of the current process
• Perform exploratory data analysis to uncover trends, patterns, and anomalies
• Generate the artifacts to showcase mapping and global transformation rules that needs to be applied to the data
• Work closely with data architects and business analysts to understand the global data reporting requirements and standards
• Validate data accuracy, completeness and integrity of the data in the source systems
• Identify and document data quality issues and discrepancies
• Provide decision-support through ad-hoc analysis, data profiling etc





