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Insurance Computer Science Jobs in Texas (NOW HIRING)

... computer science, and application-specific knowledge * Through analytic modeling, statistical ... These monetary benefits include medical insurance, life insurance, disability, paid time off ...

Data Scientist Level 3

Boerne, TX ยท On-site

$92K - $126K/yr

... computer science, and application-specific knowledge * Through analytic modeling, statistical ... These monetary benefits include medical insurance, life insurance, disability, paid time off ...

Master's or PhD in a quantitative field such as Data Science, Statistics, Computer Science, or ... We also offer 401(k), company paid life insurance, tuition reimbursement, a minimum of 18 days of ...

Senior Software Engineer

Austin, TX

$121K - $160K/yr

Solid grasp of computer science foundations, mainly algorithms and data structures * Expertise in ... Disability and Life Insurance. * 401K with company match . * Paid time off and company-paid ...

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Insurance Computer Science information

What is the difference between Insurance Computer Science vs Insurance Underwriter?

AspectInsurance Computer ScienceInsurance Underwriter
Required CredentialsDegree in Computer Science, Data Analysis certificationsDegree in Business, Finance, or Risk Management
Work EnvironmentTech-focused, data-driven, often in offices or remoteOffice setting, assessing risks, interacting with clients and agents
Employer & Industry UsageInsurance companies, tech firms, insurtech startupsInsurance carriers, brokerage firms, underwriting agencies
Common Search & ComparisonInsurance Computer Science vs Insurance Underwriter

Insurance Computer Science professionals focus on developing and managing insurance-related software, data analysis, and technology solutions. In contrast, Insurance Underwriters evaluate risks and determine policy terms. Both roles are vital in the insurance industry but differ in skills, work environment, and daily responsibilities.

What is Insurance Computer Science?

Insurance Computer Science is a specialized field that focuses on applying computer science principles, such as programming, data analysis, and systems development, to the insurance industry. Professionals in this area develop software applications, analyze large datasets, and create algorithms to streamline insurance processes like underwriting, claims management, and risk assessment. Their work helps insurance companies improve efficiency, reduce fraud, and deliver better customer experiences through technology. As digital transformation continues, the demand for computer science experts in insurance is growing rapidly.

What other jobs can I get with a computer science degree?

With a computer science degree, you can pursue roles such as software developer, data analyst, cybersecurity analyst, systems analyst, or IT consultant. These jobs often require knowledge of programming languages, problem-solving skills, and familiarity with tools like databases and operating systems.

What are some common challenges faced by computer science professionals working in the insurance industry?

Computer science professionals in the insurance industry often navigate challenges such as integrating legacy systems with modern technologies, ensuring data security for sensitive customer information, and adapting to frequent regulatory changes. Additionally, they may need to collaborate closely with actuaries, underwriters, and business analysts to develop and maintain robust software solutions that support underwriting, claims processing, and risk analysis. The fast pace of technological advancements in areas like AI, machine learning, and data analytics also requires continuous learning and adaptation.

What are the key skills and qualifications needed to thrive as an Insurance Computer Science professional, and why are they important?

To thrive as an Insurance Computer Science professional, you need a strong background in computer science principles, data analysis, and a solid understanding of insurance industry processes, typically supported by a relevant degree. Familiarity with programming languages (such as Python, Java, or SQL), data analytics tools, and insurance software systems is highly valued, and certifications like CPCU or relevant IT credentials can enhance your profile. Analytical thinking, problem-solving abilities, and effective communication are vital soft skills for collaborating with technical and non-technical stakeholders. These skills ensure the creation of robust technology solutions that optimize insurance operations and support sound business decisions.

What jobs pay 2000 a day?

In the field of insurance computer science, high-paying roles such as senior software engineers, data scientists, or cybersecurity specialists can earn around $2,000 per day, especially with extensive experience, specialized skills, and working for large organizations or consulting firms. These positions often require advanced technical knowledge, certifications, and the ability to handle complex systems or data security tasks.

What software is used in insurance companies?

Insurance computer science professionals typically work with software such as claims management systems, policy administration platforms, customer relationship management (CRM) tools, and data analysis software like SAS or SQL. They also use programming languages like Java, Python, or C++ for developing and maintaining insurance applications, along with specialized actuarial and underwriting software. Familiarity with enterprise resource planning (ERP) systems and data security tools is also important in this field.
What are popular job titles related to Insurance Computer Science jobs in Texas? For Insurance Computer Science jobs in Texas, the most frequently searched job titles are:
Data Scientist Level 3

Data Scientist Level 3

IntelliGenesis

Boerne, TX โ€ข On-site

Full-time

Medical, Life, Retirement, PTO

Posted 4 days ago


Job description

Job Duties

  • Employ some combination (2 or more) of the following skill areas:
    • Foundations: (Mathematical, Computational, Statistical)
    • Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility)
    • Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)
  • Devise strategies for extracting meaning and value from large datasets
  • Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application-specific knowledge
  • Through analytic modeling, statistical analysis, programming, and/or other appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in customer data holdings
  • Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist other with drawing appropriate conclusions from the analysis of such data
  • Effectively communicate complex technical information to non-technical audiences
  • Make informed recommendations regarding competing technical solutions by maintaining awareness of constantly shifting collection, processing, storage and analytic capabilities and limitations

Required Skills:

  • US Citizens Only
  • Active TS/SCI Clearance andย Polygraphย required
  • Information Assurance Certification may be required
  • Minimum of ten (10)ย years of relevant experience and a Bachelorโ€™s degree or twelve (12) years of relevant experience and an Associateโ€™s degree required.ย 
  • Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science
  • A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university
  • Relevant experience must be two of more of the following:
    • Designing/implementing machine learning
    • Data science
    • Advanced analytical algorithms
    • Programming (skill in at least one high-level language (e.g., Python))
    • Statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models)
    • Data management (e.g., data cleaning and transformation)
    • Data mining
    • Data modeling and assessment
    • Artificial intelligence
    • Software engineering

Compensation Range: $92,000 - $126,000

_____________________________________________________________________________________________________

Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or implied final compensation or salary for this job opening. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, candidateโ€™s scope of relevant work experience, educational background, certifications, contract-specific affordability, organizational requirements and alignment with local market data.

Our compensation includes other indirect financial components designed to support employeesโ€™ total well-being, which should be considered when evaluating our competitive benefits package. These monetary benefits include medical insurance, life insurance, disability, paid time off, maternity/paternity leave, 401(k) company match, training/education reimbursements and other work/life programs.

_____________________________________________________________________________________________________

IntelliGenesis is committed to providing equal opportunity to all employees and applicants for employment. The Company is an Equal Opportunity Employer (EOE), and as such, does not tolerate discrimination, retaliation, or harassment of its employees or applicants based upon race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or any other protected characteristic under local, state, or federal law in any employment practice. Such employment practices include, but are not limited to: hiring, promotion, demotion, transfer, recruitment, or recruitment advertising, selection, disciplinary action layoff, termination, rates of pay, or other forms of compensation and selection of training.

IntelliGenesis is committed to the fair and equal employment of individuals with disabilities. It is the Companyโ€™s policy to reasonably accommodate qualified individuals with disabilities unless the accommodation would impose an undue hardship on the organization. In accordance with the Americans with Disabilities Act (ADA) as amended, reasonable accommodations will be provided to qualified individuals with disabilities, when such accommodations are necessary, to enable them to perform the essential functions of their jobs or to enjoy the equal benefits and privileges of employment. This policy applies to all applicants for employment and all employees.

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