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Intern Data Science Insurance Jobs in Nevada (NOW HIRING)

Why this role is exciting This is a high-impact role at the intersection of data science, mapping ... Unlimited Paid Vacation Days 401(k) programme Health, Dental & Vision Insurance All Vay team ...

At Capital Insurance Group we offer our employees more than just a job. We foster career growth ... science training. CIG also supports travel to conferences that offer career development ...

Senior Data Engineer

Las Vegas, NV · On-site

$121K - $151K/yr

Requirements: * Bachelor's degree in computer science, information systems, data science ... insurance; flexible spending accounts and/or health savings accounts; dependent savings accounts ...

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Intern Data Science Insurance information

What does an Intern Data Science Insurance do?

An Intern Data Science Insurance assists data scientists and analysts in the insurance industry by collecting, cleaning, and analyzing data to help solve business problems. Their tasks often include working with large datasets, building predictive models, and creating visualizations to support risk assessment, fraud detection, and pricing strategies. They also collaborate with other departments to understand insurance processes and contribute to the development of data-driven solutions. This role offers hands-on experience with industry tools and methodologies, preparing interns for a career in data science within the insurance sector.

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

To thrive as an Intern Data Science in Insurance, you need foundational knowledge in statistics, data analysis, and programming (often with Python or R), typically supported by coursework in data science or related fields. Familiarity with data visualization tools (such as Tableau or Power BI), SQL databases, and machine learning libraries is often expected. Strong analytical thinking, attention to detail, and effective communication help you interpret data insights and collaborate with cross-functional teams. These skills are crucial for extracting actionable insights from complex insurance data and supporting data-driven decision-making within the industry.

What types of projects can an Intern in Data Science expect to work on within the insurance industry?

As a Data Science Intern in the insurance sector, you can expect to work on projects such as analyzing customer data to identify risk factors, developing predictive models for claims, or assisting in the automation of underwriting processes. These projects often involve collaboration with actuarial, underwriting, and IT teams, providing interns with exposure to different facets of the business. You'll likely use tools like Python, R, and SQL while working with real datasets, and your contributions may directly impact decision-making and operational efficiency. This hands-on experience is valuable for understanding the practical applications of data science in a highly regulated and data-driven industry.
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DATA SCIENTIST

$49K/yr

Other

Posted 2 days ago


Job description

The PALACE Acquire Program offers you a permanent position upon completion of your formal training plan. As a Palace Acquire Intern you will experience both personal and professional growth while dealing effectively and ethically with change, complexity, and problem solving. The program offers a 3-year formal training plan with yearly salary increases. Promotions and salary increases are based upon your successful performance and supervisory approval.Qualifications:BASIC REQUIREMENT OR INDIVIDUAL OCCUPATIONAL REQUIREMENT:
Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
You may qualify if you meet one of the following:
1. GS-7: You must have completed or will complete a 4-year course of study leading to a bachelor's from an accredited institution AND must have documented Superior Academic Achievement (SAA) at the undergraduate level in the following:
a) Grade Point Average 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum.
2. GS-9: You must have completed 2 years of progressively higher-level graduate education leading to a master's degree or equivalent graduate degree:
a) Grade Point Average - 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum. If more than 10 percent of total undergraduate credit hours are non-graded, i.e. pass/fail, CLEP, CCAF, DANTES, military credit, etc. you cannot qualify based on GPA.
KNOWLEDGE, SKILLS AND ABILITIES (KSAs): Your qualifications will be evaluated on the basis of your level of knowledge, skills, abilities and/or competencies in the following areas:
1. Professional knowledge of basic principles, concepts, and practices of data science to apply scientific methods and techniques to analyze systems, processes, and/or operational problems and procedures.
2. Knowledge of mathematics and analysis to perform minor phases of a larger assignment and prepare reports, documentation, and correspondence to communicate factual and procedural information clearly.
3. Skill in applying basic principles, concepts, and practices of the occupation sufficient to perform routine to difficult but well precedented assignments in data science analysis.
4. Ability to analyze, interpret, and apply data science rules and procedures in a variety of situations and recommend solutions to senior analysts.
5. Ability to analyze problems to identify significant factors, gather pertinent data, and recognize solutions.
6. Ability to plan and organize work and confer with co-workers effectively.
PART-TIME OR UNPAID EXPERIENCE: Credit will be given for appropriate unpaid and or part-time work. You must clearly identify the duties and responsibilities in each position held and the total number of hours per week.
VOLUNTEER WORK EXPERIENCE: Refers to paid and unpaid experience, including volunteer work done through National Service Programs (i.e., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community; student and social). Volunteer work helps build critical competencies, knowledge and skills that can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.Education:IF USING EDUCATION TO QUALIFY: If position has a positive degree requirement or education forms the basis for qualifications, you MUST submit transcriptswith the application. Official transcripts are not required at the time of application; however, if position has a positive degree requirement, qualifying based on education alone or in combination with experience, transcripts must be verified prior to appointment. An accrediting institution recognized by the U.S. Department of Education must accredit education. Click here to check accreditation.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying.Employment Type: OTHER