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Insurance Data Analytics Jobs in Spring, TX (NOW HIRING)

Build foundational understanding of relevant insurance and energy domain concepts. * Data Discovery, Exploration & Engineering * Conduct Exploratory Data Analysis to assess data quality, structure ...

New

Build foundational understanding of relevant insurance and energy domain concepts. * Data Discovery, Exploration & Engineering * Conduct Exploratory Data Analysis to assess data quality, structure ...

New

Build foundational understanding of relevant insurance and energy domain concepts. * Data Discovery, Exploration & Engineering * Conduct Exploratory Data Analysis to assess data quality, structure ...

... pet!) insurance as well as special perks and discounts. Learn more about Bank OZK benefits. Job ... The position focuses on risk analysis, reporting, and understanding the Bank's data inputs for ...

Duties include a proactive approach to data analysis, enabling the Marketing and eCommerce team to ... Insurance: Company-provided life insurance and short-term disability coverage. * Retirement: 401(k) ...

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Insurance Data Analytics information

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$48

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How much do insurance data analytics jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for insurance data analytics in Spring, TX is $48.72, according to ZipRecruiter salary data. Most workers in this role earn between $39.13 and $55.19 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Insurance Data Analytics position, and why are they important?

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.

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.

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 collects, processes, and analyzes insurance data to identify trends, assess risks, and support decision-making. They use tools like Excel, SQL, and data visualization software to create reports and models that improve underwriting, claims management, and pricing strategies.

How much does an insurance analyst make?

The average salary for an insurance analyst is around $65,000 to $85,000 per year, depending on experience, location, and industry. Entry-level roles typically start lower, while experienced analysts with specialized skills or certifications can earn higher salaries. Strong analytical skills and proficiency with data tools like Excel or SQL are often required.

Will AI replace a data analyst?

AI can automate routine data processing and analysis tasks, but the role of a data analyst, including those in insurance data analytics, involves interpreting complex data, providing insights, and making strategic decisions that require human judgment. Therefore, AI is more likely to augment rather than fully replace data analysts, who also need skills in data visualization, domain knowledge, and communication. Continuous learning and proficiency with analytics tools remain important for the role.

What is an Insurance Data Analytics job?

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 popular job titles related to Insurance Data Analytics jobs in Spring, TX? For Insurance Data Analytics jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Insurance Data Analytics jobs in Spring, TX look for? The top searched job categories for Insurance Data Analytics jobs in Spring, TX are:
What cities near Spring, TX are hiring for Insurance Data Analytics jobs? Cities near Spring, TX with the most Insurance Data Analytics job openings:
Infographic showing various Insurance Data Analytics job openings in Spring, TX as of June 2026, with employment types broken down into 5% As Needed, 74% Full Time, 15% Part Time, 3% Temporary, and 3% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $101,335 per year, or $48.7 per hour.
Data Engineer - Enterprise Data Engineering & Analytics

Data Engineer - Enterprise Data Engineering & Analytics

MD Anderson

Houston, TX • Remote

$109K - $131K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 166 frontline employees who took The Breakroom Quiz

32nd of 877 rated healthcare providers


Job description

The Data Engineer role is a key contributor within the Enterprise Data Engineering & Analytics Department, responsible for supporting critical digital initiatives through the design and delivery of scalable data solutions. The Data Engineer develops and maintains end-to-end data pipelines within the Context Engine, working collaboratively with cross-functional teams to ensure high-quality data integration and analytics delivery. The Data Engineer plays an essential role in accelerating access to trusted data and enabling actionable insights that support institutional priorities.
UT MD Anderson is a leading institution focused on cancer care, research, education, and prevention. The Data Engineer at UT MD Anderson contributes to advancing innovative data strategies that support clinical, operational, and research excellence, ensuring data is transformed into meaningful, secure, and reliable assets across the organization.
The ideal candidate will have a strong foundation in data engineering principles with a preferred Master's degree in Business Analytics, Computer Science, Information Technology, Data Science, or a related field. Experience building end-to-end data pipelines and familiarity with tools such as Power BI, Microsoft Fabric, and Palantir Foundry are highly desirable. Candidates with healthcare IT or clinical data experience and certifications such as Caboodle will stand out.
Minimum $106,500 - Midpoint $133,000 - Maximum $159,500
Work Location: Remote 100% within Texas
Why Us?
Working as a Data Engineer at UT MD Anderson provides the opportunity to directly impact innovative healthcare data initiatives that improve patient outcomes and accelerate research. This role offers strong collaboration with senior technical teams, continuous learning, and exposure to modern data platforms while supporting a mission-driven organization that values excellence and sustainable work-life balance.
• Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance.
• Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.
• Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.
• Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.
Responsibilities
Data Engineering - End-to-End Solution Delivery:
• Participate in end-to-end solution delivery to enhance information capabilities and data value across the institution
• Support data ingestion, ingress, egress, curation, transformation, modeling, and visualization within the Context Engine framework
• Integrate data governance processes ensuring tracking of provenance, data security, quality, and ontology
• Contribute to planning, architecture, analysis, design, and build of data pipelines in collaboration with IS, Data Offices, and governance teams
• Support pipelines across all stages from data acquisition to consumption for use-case-driven analytics
• Develop repeatable solution designs and data models supporting scalable analytics deliverables
• Build data curation pipelines including profiling, cleansing, transforming, standardizing, harmonizing, validating, and aggregating data
• Monitor and maintain data quality across enterprise systems
• Incorporate metadata management and governance standards into all data processes
• Promote modern tools, automation, and architectures to reduce manual and error-prone data integration tasks
Standards, Testing & System Maintenance:
• Adhere to IS division procedures and institutional data strategy standards including governance oversight
• Support documentation for enhancements and new technologies
• Follow change control processes and participate in change control audits
• Perform quality control, testing, and peer reviews of data solutions
• Assist in managing analytics system updates and new releases
• Ensure compliance with regulatory requirements, quality standards, and best practices
• Collaborate with internal and external stakeholders for solution validation
• Participate in after-hours support and downtime procedures
Education & Training:
• Train data scientists, analysts, and end users on data pipeline utilization and preparation techniques
• Assist in developing training plans for Context Engine tools in partnership with training teams
• Deliver institutional, departmental, and individual training on data engineering deliverables
• Support the development of training curricula with system experts
Collaboration & Customer Support:
• Build strong partnerships with Enterprise Development & Integration and Data Science teams
• Support liaison relationships across departments and IS teams
• Deliver effective technical solutions aligned with customer needs
• Provide responsive support and maintain high standards of customer service
OneIS Commitment:
• Promote integrity, trust, and respect in all interactions
• Strengthen collaborative relationships with stakeholders and team members
• Deliver innovative, high-quality, and sustainable IT solutions
• Demonstrate commitment to continuous improvement and operational excellence
EDUCATION
  • Required: Bachelor's Degree
  • Preferred: Master's Degree Business Analytics, Computer Science, Information Technology, Data Science, or related.

WORK EXPERIENCE
  • Required: 2 years Clinical, relevant healthcare information technology, or relevant business experience. or
  • Required: With preferred degree, no experience required.
  • May substitute required education with years of related experience on a one to one basis.
  • Preferred: Experience building end to end data pipelines, Power BI, Microsoft Fabric, Palantir Foundry.
  • Preferred Certification: Caboodle

LICENSES AND CERTIFICATIONS
  • Required: EPIC - EPIC Certification Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic. within 180 Days

The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
Additional Information
  • Requisition ID: 181556
  • Employment Status: Full-Time
  • Employee Status: Regular
  • Work Week: Days
  • Minimum Salary: US Dollar (USD) 106,500
  • Midpoint Salary: US Dollar (USD) 133,000
  • Maximum Salary : US Dollar (USD) 159,500
  • FLSA: exempt and not eligible for overtime pay
  • Fund Type: Hard
  • Work Location: Remote (within Texas only)
  • Pivotal Position: Yes
  • Referral Bonus Available?: No
  • Relocation Assistance Available?: No

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