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.
- Familiarity with statistical and machine learning techniques.
- Experience with data wrangling, attribute creation, model development, solution implementation and quality assurance.
- Knowledge of data visualization tools and techniques.
- Experience with SQL and data management.
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.
- Strong problem-solving skills with a willingness to learn and adapt.
- Ability to communicate ideas clearly and work collaboratively with others.
- Ability to document work clearly and practice presenting results in a team setting.
- Willingness to travel
