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Internship Insurance Data Analytics Jobs in Houston, TX

P&C Insurance Analyst

Houston, TX ยท On-site

$19 - $26/hr

The Property & Casualty Insurance Analyst provides essential support to account management ... Data Management & Analysis * Assist with data requests and maintenance of accurate policy and ...

Bachelor's degree in Business, Finance, Economics, Information Systems, or a related field * 0-2 years of professional experience in a data, analytics, or reporting role (internships and co-ops count)

Bachelor's degree in Business, Finance, Economics, Information Systems, or a related field * 0-2 years of professional experience in a data, analytics, or reporting role (internships and co-ops count)

Requirements * Bachelor's degree in data analytics, statistics, information systems, security ... Medical/ Dental/ Vision Insurance; FSA Medical & FSA Dependent Care; Pre-tax 401(k) & ROTH 401(k) ...

Manage and mentor interns, junior data scientists and analysts * Translate advanced analytics results into strategic recommendations for VP and C-level leadership * Utilize programming languages such ...

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Internship Insurance Data Analytics information

See Houston, TX salary details

$11

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

As of Aug 2, 2026, the average hourly pay for internship insurance data analytics in Houston, TX is $21.49, according to ZipRecruiter salary data. Most workers in this role earn between $16.54 and $23.41 per hour, depending on experience, location, and employer.

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

To thrive as an Insurance Data Analytics Intern, you need a solid understanding of statistics, data analysis, and basic insurance concepts, often supported by coursework in mathematics, economics, or computer science. Familiarity with tools such as Excel, SQL, Python, and data visualization platforms like Tableau is typically expected. Strong attention to detail, analytical thinking, and effective communication skills help you interpret data and present findings clearly. These skills are crucial for accurately analyzing insurance data, supporting business decisions, and contributing meaningful insights to the team.

What types of projects can I expect to work on during an Insurance Data Analytics internship?

As an Insurance Data Analytics intern, you will typically assist with analyzing large datasets to identify trends, assess risk factors, and support decision-making for underwriting or claims teams. Your daily tasks might include data cleaning, building dashboards, and generating reports using tools like Excel, SQL, or Python. You'll likely collaborate closely with experienced data analysts, actuaries, and other departments to translate data insights into actionable business strategies. These projects offer valuable exposure to industry-standard analytics practices and contribute to real business outcomes.

What is an Internship in Insurance Data Analytics?

An Internship in Insurance Data Analytics is a temporary position for students or recent graduates to gain practical experience analyzing data within the insurance industry. Interns typically assist with collecting, interpreting, and presenting data to help insurance companies make informed decisions about risk, pricing, and customer trends. The role often involves using statistical tools, working with large datasets, and supporting data-driven projects. It provides valuable exposure to both the insurance sector and the field of data analytics, helping interns develop technical and professional skills.
What are the most commonly searched types of Insurance Data Analytics jobs in Houston, TX? The most popular types of Insurance Data Analytics jobs in Houston, TX are:
What job categories do people searching Internship Insurance Data Analytics jobs in Houston, TX look for? The top searched job categories for Internship Insurance Data Analytics jobs in Houston, TX are:
What cities near Houston, TX are hiring for Internship Insurance Data Analytics jobs? Cities near Houston, TX with the most Internship Insurance Data Analytics job openings:
Infographic showing various Internship Insurance Data Analytics job openings in Houston, TX as of July 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $44,701 per year, or $21.5 per hour.

AI & Data Analytics Co-op/Intern

Amot Controls Corporation

Houston, TX โ€ข On-site

Full-time

Re-posted 26 days ago


Job description

Position Type: Co-op / Internship (Graduate-level, semester or summer term)
Location: [On-site - Houston]
Duration & Schedule: 10-12 week summer internship OR 4-8 month co-op aligned to Fall, Spring, or Summer academic terms; full-time (40 hours per week).
Key Responsibilities:
  • Engage with stakeholders across all levels of the organization to map end-to-end workflows for Sales, Customer Service, and Supply Chain functions, and translate business needs into well-scoped analytics or automation problem statements.
  • Collaborate within cross-functional teams to identify process bottlenecks and propose intelligent automation opportunities, prioritizing solutions based on business impact, feasibility, and time-to-value.
  • Leverage AI tools such as Microsoft Copilot and Claude to accelerate analysis, prototyping, and solution development, while applying sound judgment about when AI assistance is appropriate.
  • Contribute to the design, development, and deployment of internal AI chatbots and autonomous agents within the Microsoft Azure ecosystem (Azure AI Foundry, Azure OpenAI, Copilot Studio, Power Platform) to improve productivity and service levels.
  • Build evaluation datasets, design test cases, and measure the quality, accuracy, and safety of deployed AI agents.
  • Support adoption through training, documentation, and change-management support.
  • Document architectures, workflows, prompts, and lessons learned so that work is reproducible and transferable.

Required Qualifications and Experience:
  • Currently pursuing a Master's degree (or in the final year of an undergraduate program transitioning to graduate study) in Information Systems, Computer Science, Data Analytics, Data Science, Business Analytics, Industrial Engineering, or a related field.
  • Foundational programming skills in Python, including familiarity with libraries such as pandas, NumPy, and at least one visualization or ML library.
  • Working knowledge of SQL - able to write joins, aggregations, and window functions against a relational database.
  • Conceptual understanding of large language models (LLMs), prompt engineering, and retrieval-augmented generation (RAG).
  • Strong analytical and problem-solving skills with a business-oriented mindset; able to frame ambiguous problems and structure an approach.
  • Clear written and verbal communication skills, with the ability to explain technical concepts to non-technical stakeholders.

Preferred Qualifications and Experience:
  • Hands-on experience with Power BI (DAX, Power Query) or another enterprise BI tool.
  • Exposure to the Microsoft Azure AI stack - Azure AI Foundry, Azure OpenAI, Azure AI Search, or Cognitive Services.
  • Experience building automations with Power Automate, Copilot Studio, or similar low-code platforms.
  • Familiarity with version control (Git), Jupyter notebooks, and basic software engineering hygiene.
  • Coursework, projects, or internships involving applied machine learning, NLP, or generative AI.
  • Prior exposure to manufacturing, industrial, or B2B operations is a plus but not required.

What You Will Gain:
  • Real ownership of AI and analytics deliverables that are used by AMOT employees and influence operational decisions.
  • Practical experience deploying AI solutions in an industrial manufacturing environment, including governance, security, and adoption considerations.
  • A portfolio of measurable outcomes suitable for academic capstones, theses, or future job applications.

Other:
  • Physical Requirements: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this Job, the employee is regularly required to sit; use hands/fingers to handle, or feel and talk or hear. The employee is occasionally required to stand; walk and reach with hands and arms. The employee must regularly lift and/or move up to 25 pounds and occasionally lift and/or move up to 40 pounds. Specific vision abilities required by this job include close vision, distance vision, color vision and ability to adjust focus.
  • Working Conditions: The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this Job, the employee is occasionally exposed to moving mechanical parts; fumes or airborne particles; toxic or caustic chemicals and risk of electrical shock when in the operations or laboratory areas. The noise level in the work environment is usually moderate, but due to open office environment noise level may occasionally be high.

Disclaimer: The above information on this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job. EOE/AA/M/F/Vet/Disability
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.