LexisNexis Risk Solutions needs to extract knowledge and insights from high-volume, high-dimensional data to investigate complex business problems within the insurance vertical, aiming to provide solutions and decision tools that help customers evaluate and predict risk and enhance operational efficiency.
Requirements
- Working knowledge of standard data languages (e.g. Python, R, etc..)
- Basic understanding of best practices in data integrity and manipulation.
- Experience in cloud environment a plus.
- Willingness to learn new technical skills and industry domain knowledge.
Responsibilities
- Extracting knowledge and insights from high-volume, high-dimensional data to investigate complex business problems.
- Utilize a range of data preparation, modeling, analysis, and visualization techniques, including statistical analysis, predictive modeling, and pattern recognition.
- Using existing data platforms and tools such as ERP/CRM systems, relational or NoSQL databases, and data analysis and visualization software.
- Develop your own scripts and visualizations using object-oriented programming to enhance data insights and solutions.
- Primarily provide support to more senior Data Scientists
- Pulls data, cleans data, builds and maintains existing models
- Participates in result presentation to internal stakeholders
Other
- Bachelor’s degree in a quantitative field such as Statistics, Applied Math, Computer Science or a related quantitative field
- Proven work experience in Data, Analytics, or Insurance OR Master’s degree in Actuarial Science, Statistics, or Data Science.
- Have a desire to help solve complex problems.
