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Insurance Data Analytics Jobs in Colorado (NOW HIRING)

Apex Systems

Data Analyst

Greenwood Village, CO · On-site

Job#: 3051114 Data Analyst Location: Greenwood Village, Colorado (Hybrid) Role Overview This role ... other insurance plans that offer an optional layer of financial protection. We offer an ESPP ...

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Crusoe

Strategic Sourcing Data Analyst

Denver, CO · On-site

Experience: 2-4 years of experience in data analytics, preferably within the supply chain ... Paid life insurance, short-term and long-term disability * Professional development & tuition ...

Crusoe

Strategic Sourcing Data Analyst

Denver, CO · On-site

Experience: 2-4 years of experience in data analytics, preferably within the supply chain ... Paid life insurance, short-term and long-term disability * Professional development & tuition ...

Surgery Partners

Clinical EHR Data Analyst

Durango, CO · On-site

$24.87 - $49.85/hr

BSN required; BS in Data Analytics, Data Science, CIS, or equivalent experience preferred ... insurance with 401k with employer matching Animas Surgical Hospital is a drug free workplace and ...

Surgery Partners

Clinical EHR Data Analyst

Durango, CO · On-site

$24.87 - $49.85/hr

BSN required; BS in Data Analytics, Data Science, CIS, or equivalent experience preferred ... insurance with 401k with employer matching Animas Surgical Hospital is a drug free workplace and ...

Crusoe

Senior Strategic Sourcing Data Analyst

Denver, CO · On-site

$88K - $111K/yr

Experience: 5-7 years of experience in data analytics, preferably within the supply chain ... Paid life insurance, short-term and long-term disability * Professional development & tuition ...

Crusoe

Senior Strategic Sourcing Data Analyst

Denver, CO · On-site

$88K - $111K/yr

Experience: 5-7 years of experience in data analytics, preferably within the supply chain ... Paid life insurance, short-term and long-term disability * Professional development & tuition ...

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Insurance Data Analytics information

What is insurance data analytics?

An Insurance Data Analytics job involves analyzing large volumes of insurance-related data to identify trends, assess risks, detect fraud, and improve decision-making. Professionals in this field use statistical models, machine learning, and data visualization tools to extract insights that help insurers optimize pricing, enhance customer experience, and reduce losses. They work with claims data, policyholder information, and external data sources to drive business strategy. Strong analytical skills, proficiency in data tools like SQL, Python, or R, and knowledge of insurance principles are essential for success in this role.

What are the typical responsibilities of someone working in insurance data analytics?

Professionals in Insurance Data Analytics are responsible for collecting, cleaning, and analyzing large sets of insurance-related data to identify trends, assess risk, and inform business decisions. They commonly develop predictive models, generate reports, and provide actionable insights that help underwriting teams, actuarial staff, and business leaders optimize processes or pricing strategies. Day-to-day tasks may also include collaborating with IT and business units to define data requirements, presenting findings to non-technical stakeholders, and ensuring data integrity. This role often involves a mix of independent analysis and team-oriented projects, offering a dynamic and engaging work environment for problem solvers.

What are the key skills and qualifications needed to thrive in insurance data analytics?

To thrive in Insurance Data Analytics, you need a solid understanding of data analysis, statistics, and insurance industry concepts, usually supported by a degree in mathematics, statistics, finance, or a related field. Proficiency with analytical tools like SQL, Python, R, and data visualization platforms (such as Tableau or Power BI), as well as certifications like CPCU or advanced analytics credentials, are highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts translate complex data into actionable business insights. These skills are crucial for driving informed decision-making, risk assessment, and operational improvements within insurance organizations.

How is data analytics used in insurance?

In insurance, data analytics is used by professionals to assess risk, set premiums, detect fraud, and improve customer segmentation. Analysts utilize tools like statistical models and machine learning algorithms to interpret large datasets, enabling more accurate underwriting and claims management. Strong analytical skills and knowledge of data visualization are essential for effective decision-making in this field.

What does a data analyst do in insurance?

An insurance data analyst examines large datasets to identify trends, assess risk, and support decision-making processes within insurance companies. They use tools like Excel, SQL, and data visualization software to interpret claims, policy data, and customer information, helping improve underwriting, pricing, and fraud detection.

What are the most commonly searched types of Insurance Data Analytics jobs in Colorado?

The most popular types of Insurance Data Analytics jobs in Colorado are:

What are popular job titles related to Insurance Data Analytics jobs in Colorado?

For Insurance Data Analytics jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Insurance Data Analytics jobs in Colorado look for?

The top searched job categories for Insurance Data Analytics jobs in Colorado are:

What cities in Colorado are hiring for Insurance Data Analytics jobs?

Cities in Colorado with the most Insurance Data Analytics job openings:

Insurance Data Analytics jobs near you
Infographic showing various Insurance Data Analytics job openings in Colorado as of September 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 81% In-person, 6% Hybrid, and 13% Remote job distribution.

Data Scientist - GEOINT Analysis

Colorado Springs, CO • On-site

Assertive Professionals
Guided Missile and Space Vehicle Manufacturing • 11 - 50 employees
Learn more about Assertive Professionalsexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago

Job description

Assertive Professionals is seeking a Data Scientist supporting our National Security customer in Colorado Springs, CO.
This is a proposed position, we are offering a salary of $160,000 with a $2,000 sign-on bonus, or reimbursable relocation.
This is a great opportunity to work for an employee-centric, fast-growing small business. We offer an excellent benefits package, including PTO (accrual rates vary by contract and customer requirements), 401(k) Match at 5%, Profit Sharing, Company-paid Life Insurance, Dental, Vision, STD/LTD, and two options under a national medical plan with employee contribution.There is an additional $1,200 annual corporate bonus for time and attendance compliance!
Responsibilities Include:
This position is responsible for conducting data science functions on structured and unstructured data to streamline intelligence analysis and production. The data scientist will work to enrich analytical results and will develop and maintain Python code in support of mission requirements.
Required Experience and Qualifications:
  • TS/SCI w/ CI Poly
  • 7 years of relevent experience
  • Demonstrate experience and knowledge of computer science concepts, data architecture, intelligence practices, and managing data in a big-data environment.
  • Demonstrate expert knowledge of Python, and Jupyter Notebooks and/or JupyterLabs.
  • Author cogent and logical scripts using Python and other applicable languages in a virtual environment using common Integrated Development Environments (IDE) such as VS Code, Spyder, PyScript, or Jupyter Notebooks.
  • Develop and use advanced software programs, algorithms, querytechniques, models to solve complex intelligence problems, and automated processes to normalize, integrate, and evaluate data.
  • Debug existing and future Python code; refactor legacy code to ensure continued security, functionality, and compatibility.
  • Document and block-comment all code to ensure recoverability and error-checking, and enhance reading, checking, and maintaining code in accordance with common data science and coding standards, such as PEP-8 for Python,5 or using style-guide features embedded in common IDE applications, such as Spyder, VS Code, PyScript or others upon approval by the Government.
  • Collaborate across multi-discipline teams to ensure connectivity between various data sources and business problems.
  • Identify meaningful insights, interpret, and communicate findings, plus make recommendations to stakeholders.
  • Analyze requirements and evaluate technologies for data science capabilities including Natural Language Processing, Machine Learning, predictive modeling, statistical analysis, and hypothesis testing.
  • Maintain awareness of emerging analytics and big-data technologies.
  • Complete required course NSA NETA1400 (Technology Fundamentals for Analysis); recommended completion of any of the following NSA Courses: NETA2402/NETA2108 (Analysis II), RPTG2238, RPTG2235, RPTG3225, RPTG3222 (Basic Analytical Reporting) or equivalent curriculum.
  • Complete recommended certifications: Data Science Council of America (DASCA) certifications, such as Associate Big Data Engineer (ABDE), Associate Big Data Analyst (ABDA), and Senior Data Scientist (SDS); Google Data Analytics Professional Certificate; IBM Data Science Professional Certification.

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