LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle all while reducing risk.
Requirements
- Coursework or project experience in Python or R; familiarity with SQL is a plus
- Interest in data analysis, predictive modeling, and machine learning.
- Exposure to data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) is desirable.
- Strong problem-solving skills with a willingness to learn and adapt.
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 in data science, Math, Stats, Comp Sci, or other quantitative/applied math field.
- Ability to communicate ideas clearly and work collaboratively with others.
- The role will be Hybrid located at our headquarters in Alpharetta, GA and may include some travel.
- Document work clearly and practice presenting results in a team setting.
