LexisNexis Risk Solutions is looking to solve the problem of assessing risk in the insurance industry by providing customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics.
Requirements
- Coursework or project experience in Python or R;
- Familiarity with SQL is a plus
- Exposure to data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) is desirable.
- Interest in data analysis, predictive modeling, and machine learning.
- Strong problem-solving skills with a willingness to learn and adapt.
- Ability to communicate ideas clearly and work collaboratively with others.
- Hold a bachelor’s in data science, Math, Stats, Comp Sci, or other quantitative/applied math field.
Responsibilities
- Assist with assembling, cleaning, and organizing large datasets to prepare them for analysis.
- Support team members in merging and parsing data to uncover trends and patterns.
- Learn to apply statistical and machine learning techniques under the guidance of senior analysts.
- Help document model code, track results, and contribute to validating predictive models.
- Assist in creating attributes and rules from raw data to support analytic projects.
- Contribute to data visualization efforts to communicate findings.
- Participate in preparing responses to client inquiries regarding data, score calculations, or analytic outputs.
Other
- Hold a bachelor’s degree
- Ability to communicate ideas clearly and work collaboratively with others.
- Strong problem-solving skills with a willingness to learn and adapt.
- Travel may be required
- Ability to work in a team setting and present results clearly
