Mercury Insurance is looking to solve business problems by identifying opportunities, answering business questions, and developing business solutions through data analysis and machine learning.
Requirements
- At least 2 years of experience in data mining and data/statistical analysis.
- At least 2 years experience with SQL and statistical software packages (Python, R, SAS) required.
- Demonstrated solid skills in data mining, machine learning, programming and optimization.
- Knowledge with cloud-based advanced data and analytics environment.
- Experience using R, Python and other programing languages.
- Strong data skills and the ability to work with large structured and unstructured data sources.
- Experience in of predictive modeling, general model building, and validation procedures.
Responsibilities
- identify and use relevant data sources to conduct project work and ad-hoc analyses using statistical and machine learning algorithms.
- Collect data from different applications and data infrastructure.
- Extract, transform and load large amount of structured or unstructured data from various sources.
- Apply data manipulation techniques to clean and prepare data for analysis.
- Review data for quality and consistency and optimize data retrieval methods when needed.
- Create and maintain reports, graphs and charts through dashboard and other programming and MS Excel.
- Support automated procedures to help reduce cost and improve efficiency.
Other
- The candidate will also need to collaborate with cross-functional teams of software engineers, data analysts and product leaders on business initiatives.
- The team member will work with various business departments to understand their business processes and needs.
- The team member will communicate and collaborate with colleagues and managers regarding analysis needs and results.
- Communicates effectively and regularly with SMEs, EBI, MTS, and Management in the various functional areas to learn about each job function.
- Creates presentations summarizing problems identified, potential solutions.
