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Remote Insurance Data Analytics Jobs in Coram, NY

EnthuZiastic

Growth Hacker - Remote

Bridgeport, CT · Remote

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Orion Placement

Insurance Coverage Attorney

Bridgeport, CT · On-site +1

$100K - $198K/yr

Work directly with clients and provide strategic coverage analysis, opinions, and recommendations ... a remote role. Candidates may be located anywhere in Connecticut; however, residence near Rocky ...

Cleaning Contracts

Sales Analyst

Fairfield, CT · On-site +1

$75K - $95K/yr

🔍 About the Role We're seeking a data-driven Sales Analyst with sharp business acumen and a ... remote options available) * Health, dental & vision insurance * 401(k) with company match

Demand.com

Marketing Director (Remote)

Bridgeport, CT · Remote

DemandFactor is a data-driven B2B growth and demand-generation company helping brands find, engage ... Manage marketing KPIs, analytics, attribution, and budget * Build and grow the marketing team What ...

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All JobsInsurance Data Analytics JobsRemote Insurance Data Analytics JobsRemote Insurance Data Analytics Jobs in Coram, NY

Remote Insurance Data Analytics information

See Coram, NY salary details

$25

$56

$96

How much do remote insurance data analytics jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for remote insurance data analytics in Coram, NY is $56.08, according to ZipRecruiter salary data. Most workers in this role earn between $45.05 and $63.51 per hour, depending on experience, location, and employer.

What is the difference between Remote Insurance Data Analytics vs Remote Insurance Underwriter?

AspectRemote Insurance Data AnalyticsRemote Insurance Underwriter
Required CredentialsBachelor's in Data Science, Statistics, or related field; often certifications in data analysis or analyticsBachelor's in Business, Finance, or related; often requires insurance licensing or certifications
Work EnvironmentPrimarily data analysis, modeling, and reporting; often collaborative with IT and actuarial teamsAssessing risks, reviewing applications, making underwriting decisions; involves communication with agents and clients
Employer & Industry UsageUsed across insurance companies, reinsurers, and brokers for data-driven decision makingUsed by insurance carriers to evaluate and approve policies

Remote Insurance Data Analytics focuses on analyzing insurance data to inform business decisions, while Remote Insurance Underwriters evaluate individual insurance applications to determine coverage. Both roles are essential in the insurance industry but differ in daily tasks and required skills.

What is remote insurance data analytics?

Remote insurance data analytics is the practice of analyzing insurance-related data, such as claims, risk assessments, and customer information, from a location outside of a traditional office setting. Professionals in this field use statistical methods, data mining, and machine learning tools to identify patterns, detect fraud, and help insurance companies make data-driven decisions. This remote role often requires proficiency in data analysis tools like SQL, Python, or R, and a strong understanding of insurance industry concepts. Remote insurance data analysts collaborate with teams virtually to provide insights and support business strategies, making it a flexible career option.

How do remote insurance data analytics professionals typically collaborate with cross-functional teams to drive business insights?

Remote Insurance Data Analytics professionals often work closely with underwriters, actuaries, claims managers, and IT teams to gather data requirements, interpret findings, and implement data-driven solutions. Collaboration usually happens through virtual meetings, collaborative dashboards, and project management tools to ensure clear communication and alignment on objectives. This cross-functional approach helps identify trends, optimize risk assessments, and support strategic decision-making within the organization. Building strong relationships with team members across departments is key to successfully translating analytical results into actionable business strategies.

What are the key skills and qualifications needed to thrive as a remote insurance data analytics professional?

To excel in Remote Insurance Data Analytics, you need strong analytical skills, a background in statistics or mathematics, and typically a degree in data science, actuarial science, or a related field. Familiarity with data analysis tools like SQL, Python, R, and specialized insurance analytics platforms such as SAS or Tableau, as well as relevant certifications, is highly valuable. Attention to detail, problem-solving abilities, and effective communication set candidates apart in this role. These skills are crucial for transforming complex insurance data into actionable insights that drive informed business decisions and risk assessments.
What are popular job titles related to Remote Insurance Data Analytics jobs in Coram, NY? For Remote Insurance Data Analytics jobs in Coram, NY, the most frequently searched job titles are:
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Remote Insurance Data Analytics jobs near you

Technical Clinical Data Manager /Data Analyst (Remote)

Penfield Search Partners

Fairfield, CT • Remote

Full-time

Posted 9 days ago

Job description

Contact: Neisha Camacho/Terra Parsons -
No 3rd party candidates

We are partnering with a growing biotech organization seeking a Clinical Data Manager/Data Analyst to support ongoing and upcoming clinical programs across multiple therapeutic areas.

This role will sit within a highly collaborative clinical development team and is ideal for a hands-on, analytical Clinical Data Manager who enjoys digging into the data, identifying trends or issues proactively, and developing creative solutions to improve data quality and study execution. The client is seeking someone resourceful and technically curious — not just process-oriented — with the ability to independently explore datasets, generate meaningful reports, and surface potential issues early.

The ideal candidate will bring a blend of traditional clinical data management expertise along with strong data review, querying, and analytical skills. Experience with R, SQL, SAS, or other data interrogation and reporting tools is highly desirable.

Key Responsibilities

  • Support clinical data management activities across studies from start-up through database lock
  • Perform hands-on data review and exploratory analysis to identify data trends, inconsistencies, missing data patterns, and potential study risks
  • Develop custom reports, listings, and data visualizations to support proactive data cleaning and study oversight
  • Utilize R, SQL, SAS, or similar tools to query, analyze, and troubleshoot clinical datasets
  • Partner with CROs and vendors to ensure high-quality, timely data delivery
  • Collaborate cross-functionally with Clinical Operations, Biostatistics, Statistical Programming, Medical, and Safety teams on data review strategies and issue resolution
  • Contribute to development and review of key deliverables including:
    • Data Management Plans (DMPs)
    • eCRF design and completion guidelines
    • Edit checks and query logic
    • User Acceptance Testing (UAT)
    • Data review plans and cleaning processes
  • Support ongoing query management and ensure data integrity, consistency, and inspection readiness
  • Assist with implementation of data standards, reporting enhancements, and process improvements
  • Work independently to investigate data anomalies and recommend practical solutions in a fast-paced biotech environment

Qualifications

  • BS in a scientific, technical, or clinical discipline
  • Approximately 5–8 years of clinical data management experience within biotech, pharma, or CRO environments
  • Strong hands-on experience reviewing and interrogating clinical trial data
  • Experience using R, SQL, SAS, or other querying/reporting tools to analyze clinical data and generate custom reports
  • Experience with EDC systems such as Medidata Rave, Oracle, or Veeva
  • Working knowledge of CDISC standards (SDTM/ADaM) and downstream data usage
  • Experience supporting Phase II and/or III clinical trials; CNS experience is a plus
  • Exposure to CRO/vendor oversight
  • Understanding of clinical data structures and dictionaries including MedDRA and WHODrug
  • Strong critical thinking and problem-solving skills with the ability to work independently
  • Resourceful, proactive, detail-oriented, and comfortable operating in a dynamic biotech environment
  • Strong communication and cross-functional collaboration skills