Director of Data Science

Director of Data Science

Requirements

• 8+ years of relevant analytical experience recommended.
• Master’s or Ph.D. in Statistics, Applied Mathematics, Quantitative Economics, Actuarial Science, Data Science, Computer Science, or a similar analytical field, or progress towards a relevant professional designation (e.g. FCAS, FSA, CSPA)
• Expertise in statistical modeling, inference, and building machine learning algorithms in Python and/or R.
• Expertise in the end-to-end modeling lifecycle, from requirements gathering to monitoring and validation.
• Experience with managing Data Scientists and providing guidance through model development.
• Experience in SQL and navigating databases to extract relevant attributes.
• Experience in Unix, Git, Shiny and R Markdown is a plus.
• Experience building modeling solutions in cloud-native environments, such as Sagemaker, a plus.
• Able to communicate effectively with both technical and non-technical audiences.
• Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution.
• Experience with leading project execution and driving change to core business processes through the innovative use of quantitative techniques, including the use of Artificial Intelligence.
• Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Responsibilities

• Manage a team of data scientists and actuaries that provide flexible modeling support to the development, testing and validation of loss models across both Business and Personal Insurance.
• Lead the ideation, build and implementation of Artificial Intelligence use cases across the Actuarial organization.
• Think creatively to envision how we can enhance long-standing actuarial methodology using statistical modeling and machine learning techniques.
• Create and oversee the team’s work on statistical models, algorithms, and machine learning techniques to enhance traditional actuarial processes and assumptions.
• Collaborate and partner with business stakeholders in a way that supports the vision and sustains a culture that treats analytics as a corporate asset.
• Advance the department’s capabilities by creating and deploying long-term tools to continually evolve the practice of data science, with an ability to see the end-to-end solution.
• Develop strategies to achieve targeted business objectives. Implement these strategies and follow through to successful conclusion.
• Remain current on research techniques and become familiar with state-of-the-art tools applicable to your function.
• Participate in the talent management process for hiring, onboarding, training, and development of staff.
• Collaborate with your leader to provide timely feedback on development and opportunities for your team.
• Learn/bring best practices to guide the direction of our Data Science and Data Engineering workflow.

Preferred Qualifications

• Experience in Unix, Git, Shiny and R Markdown is a plus.
• Experience building modeling solutions in cloud-native environments, such as Sagemaker, a plus.