Senior Data Scientist

Senior Data Scientist

Requirements

• 4+ years’ industry experience in data science and insurance pricing/ratemaking roles, with a deep understanding of both.
• Deep understanding and experience with advanced statistics and modern machine learning techniques such as GLMs, decision trees, forests, boosted ensembles, etc. Deep understanding of principles of insurance ratemaking.
• Superior coding skills using common data science tools, such as Python, R, Shiny, SQL, PowerBI, Excel or other statistical programming languages, etc
• Excellent skill and significant experience in data engineering and processing using SQL, Hive, Impala, Spark, or equivalent querying language
• Strong experience with distributed storage and big data computing technology, such as AWS, Hadoop, or Spark
• Actuarial FCAS or advanced degree in a quantitative discipline, such as statistics, data science, computer science, mathematics, economics, etc.
• Intellectual curiosity and ability to thrive in a team environment that is constantly changing
• Demonstrated ability to learn new technical concepts and to adapt to new technologies quickly
• Ability to communicate in a clear, concise, professional oral or written manner, to be understood by technical and non-technical colleagues.

Responsibilities

• Leads collaborations with State Management, Product Management, Finance, Technology, and Pricing to identify and define analytic initiatives, formulate strategies, design rating plan structural enhancements, and develop solutions to achieve business goals through effective use of data and pricing and machine learning models.
• Interprets and communicates data findings and insights using visualization, formal presentations, written memos, and other appropriate formats.
• Leads the preparation of statistical exhibits from pricing, research, or loss reserve analyses for internal management decision making or to fulfill statutory reporting requirements.
• Identifies appropriate actuarial, statistical, and machine learning methods for assigned work. Reviews methodologies of other analysts.
• Identifies, extracts, aggregates, and synthesizes data using SQL, R, SAS, Python or other appropriate languages to enable analysis, model development, and solution deployment.
• Applies actuarial and data science skills to analyze large, complex datasets and identify meaningful patterns that lead to actionable insights and data-driven solutions to business problems.
• Builds, tests, and validates pricing, econometric, statistical, and machine learning models and analyses using Python, R, or other appropriate language as part of overall solution development.
• Leads implementation of analytic solutions into reporting platforms or production systems by leading the solution design, development, testing, and monitoring.
• Discovers, analyzes, evaluates, and leads adoption of new data or new uses for existing data to improve the quality, efficiency, and business value of data and analytic solutions.
• Discovers, analyzes, evaluates, and leads adoption of new pricing and data science methods to improve the quality, efficiency, and business value of data and analytic solutions.
• Assists with developing department business plans. Reviews plans periodically to achieve efficiency where possible. Monitors results against specific goals to ensure completion and business impacts are achieved.
• Develops and executes project plans, tracking to defined timelines and escalating issues and blockers.
• Develops and adheres to documentation, project management, coding, and development best practices.

Preferred Qualifications

No preferred qualifications provided.