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
- Have experience in programming: exceptional Python or R abilities, experience with imperative programming languages, such as Java and SQL, data visualization is ideal.
Responsibilities
- Assembling, cleaning, merging, and parsing Big Data files to detect meaningful trends and predictive pattern
- Conducting analysis in support of existing and new product development, and/or customer sales
- Developing predictive solutions (with direction), documents model code, and work with internal or external stakeholders to validate predictive value of data driven solutions
- Developing attributes, filtering rationale and rules from raw data sources to support multiple machine learning approaches
- Providing support for client inquiries regarding score calculations, model performance or other analytic output
- Understanding and following analytic plans by identifying and executing the appropriate analytical technique
- Documenting clearly and communicating analytic work and/ or results
Other
- Hold a MS level education in Data Science, Math, Stats, Comp Sci, or other quantitative/applied math field.
- Have problem solving and communication skills
