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Insurance Data Processing Jobs in New York (NOW HIRING)

Data Scientist

Manhattan, NY

$128.82K - $138.82K/yr

This position will assess, maintain, and enhance existing data process and reporting routines and ... Health care insurance background is required. * 3-5 years required experience in progressively ...

Data Scientist

Manhattan, NY · On-site

$128.82K - $138.82K/yr

This position will assess, maintain, and enhance existing data process and reporting routines and ... Health care insurance background is required. * 3-5 years required experience in progressively ...

Data Scientist II

New York, NY · Hybrid

$131.20K - $172.20K/yr

... or data processing Bonus points: * Master's degree in a quantitative or technical field * Knowledge of or previous work experience in health care or health insurance * Experience mentoring or ...

Senior Data Scientist

New York, NY · Hybrid

$163.94K - $215.18K/yr

... data processing Bonus points: * Advanced degree in a quantitative or technical field * Experience in the healthcare, finance and/or insurance industries * Experience evaluating consumer-facing ...

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Insurance Data Processing information

What are the key skills and qualifications needed to thrive as an Insurance Data Processing Specialist, and why are they important?

To thrive as an Insurance Data Processing Specialist, you need strong attention to detail, proficiency in data entry, and a solid understanding of insurance terminology, typically supported by a high school diploma or relevant associate degree. Familiarity with insurance management software, claims processing systems, and database tools such as Microsoft Excel is commonly required. Excellent organizational skills, problem-solving abilities, and effective communication help you excel in managing large volumes of sensitive information. These skills ensure accuracy, minimize errors, and support efficient operations within insurance organizations.

What are some common challenges faced in an Insurance Data Processing role and how can they be addressed?

One of the main challenges in Insurance Data Processing is managing large volumes of sensitive data accurately and efficiently, especially when dealing with tight deadlines and evolving regulatory requirements. Errors in data entry or processing can impact claims or policy management, making attention to detail and strong organizational skills essential. To address these challenges, many teams rely on robust data management software, regular training, and collaborative workflows to ensure accuracy and compliance. Proactively seeking feedback and staying updated on industry best practices can also help professionals excel in this role.

What is Insurance Data Processing?

Insurance Data Processing refers to the collection, entry, management, and analysis of data related to insurance policies, claims, customers, and transactions. Professionals in this field use specialized software and systems to ensure that insurance information is accurate, up-to-date, and secure. Their work supports the smooth operation of insurance companies by helping to process claims, issue policies, and generate reports for decision-making. Accuracy and attention to detail are crucial in this role due to the sensitive nature of insurance data.

What is the difference between Insurance Data Processing vs Insurance Claims Processing?

AspectInsurance Data ProcessingInsurance Claims Processing
Required CredentialsTypically high school diploma or equivalent; some roles may require certifications in data managementHigh school diploma or equivalent; often requires knowledge of claims procedures and insurance policies
Work EnvironmentOffice setting, working with databases and data entry systemsOffice environment, interacting with claim documents and insurance systems
Employer & Industry UsageInsurance companies, third-party administrators, data service providersInsurance companies, claims adjusters, third-party claims processors

Insurance Data Processing involves managing and organizing insurance-related data, focusing on data accuracy and database management. Insurance Claims Processing centers on evaluating and processing insurance claims submitted by policyholders, ensuring proper documentation and compliance. While both roles support insurance operations, Data Processing emphasizes data management, whereas Claims Processing focuses on claim evaluation and settlement.

What are popular job titles related to Insurance Data Processing jobs in New York? For Insurance Data Processing jobs in New York, the most frequently searched job titles are:
What job categories do people searching Insurance Data Processing jobs in New York look for? The top searched job categories for Insurance Data Processing jobs in New York are:
What cities in New York are hiring for Insurance Data Processing jobs? Cities in New York with the most Insurance Data Processing job openings:

$116.10K - $139.40K/yr

Other

Posted 6 days ago


Job description

Remote position with the ability to travel to our NJ and NY locations up to 25% of the time.

Position Summary: Data Engineer with previous experience in the insurance domain, design, build, and maintain scalable data pipelines and models that power analytics and Generative AI initiatives. The Data Engineer will collaborate closely with analysts and engineers, to understand data needs, develop efficient solutions, and ensure the integrity, performance, and security of our data systems.

Essential Duties and Responsibilities:
  • Analyze integration and system requirements by understanding business needs and designing effective data solutions, particularly for Guidewire Policy, Billing Center and Commercial P&C data domains.
  • Design, develop, and optimize ELT pipelines to ingest, transform, and load data into a Delta Lakehouse platform.
  • Design, Develop and maintain data models and schemas ensuring data quality and integrity.
  • Build and maintain dashboards and reports delivering actionable business insights.
  • Monitor pipeline and storage performance; troubleshoot and resolve data issues promptly.
  • Collaborate with cross-functional teams, including analysts and business users, to deliver end-to-end insurance data solutions.
  • Implement data governance, security, and compliance standards across platforms.
  • Conduct root cause analysis for system failures and performance events; drive continuous improvements in enterprise data integration pipelines.
  • Create and manage testing procedures (unit, scenario, end-to-end) to ensure pipeline reliability.
  • Stay current with emerging technologies and recommend improvements to workflows.
  • Mentor team members on data engineering tools, Guidewire data model concepts and best practices.
  • Build and maintain data pipelines to process structured and unstructured data (like documents and text) for Generative AI tasks, including creating embeddings and working with vector databases to support AI search features.
  • Prepare and clean large datasets to ensure high-quality inputs for training and fine-tuning Generative AI models.
  • Collaborate with AI and data science teams to understand data requirements and deliver scalable solutions that support model training and inference.
  • Implement processes to enrich data with metadata and context to improve AI model accuracy and relevance.
  • Optimize data storage and retrieval methods to support fast, low-latency responses for AI-powered applications.
  • Monitor data workflows for Generative AI projects, troubleshooting issues, and ensure continuous pipeline performance.
Education and Experience:
  • Bachelor’s degree in relevant field of study required(e.g. computer science, data science, data analytics, applied mathematics, etc.)
  • 5+ years of progressive work experience in IT or a related field required.
  • 3+ years of experience in data engineering and analytics, with a solid foundation in data architecture and integration, including hands-on work with complex enterprise P& C Insurance data models required.
  • 2+ years of experience with data-centric projects within the Guidewire ecosystem, including working with Guidewire Policy Center and related data structures required.
  • In-depth understanding of relational database systems (e.g., Oracle, SQL Server, MySQL), including their features and performance optimization strategies.
  • Solid grasp of ETL processes, data pipeline architectures, and data integration techniques, particularly for operational source systems such as Guidewire.
  • 2+ years of hands-on experience with Azure Databricks, Azure data factory including developing and optimizing data pipelines using Apache Spark required.
  • 2+ years of experience working with Power BI or other leading data visualization and reporting tools required.
  • Proven expertise with Apache Spark, Delta Lakehouse, and data warehousing technologies required.
  • Proficient in Microsoft Azure services, including:
    • Azure SQL Database
    • Azure Data Lake Storage Gen2
    • Azure Event Grid
    • Azure Key Vault
  • Strong understanding of CI/CD pipelines and experience in Agile development environments.
  • Demonstrated ability to troubleshoot system issues, identify root causes, and implement effective solutions quickly.
  • Capable of managing multiple priorities with strong attention to detail and follow-through.
  • Working knowledge of Generative AI frameworks and use cases in data engineering is a plus.
  • Knowledge of data governance, metadata management, and data quality frameworks.
  • Understanding of data security and privacy principles, including encryption, anonymization, and access control mechanisms.
  • Proficient in Microsoft Office Suites
Skills:
  • Strong understanding of the Insurance Domain and Experience using Guidewire CDA data model to build use case specific datasets.
  • Data Modeling
  • Expertise in Azure Databricks, Azure Data Factory, Apache Spark, and data pipeline development for scalable data engineering solutions
  • Collaboration with cross-functional groups
  • Strong analytical and problem-solving skills, with the ability to translate business requirements into practical data solutions.

The salary range for this role is $86,800 - $160,700. The listed annual salary range posted for this position is subject to change and may vary depending on performance, education, experience, skills, geographic location, travel requirements, demonstrated proficiency in the competencies required for the role and business needs.  Base pay is just one component of GNY’s total compensation package for employees. Other rewards include eligibility for an annual discretionary bonus based on performance.