Overview

Verisk has developed an enterprise analytics platform that enables data scientists across the company to do R&D and Analytics on our proprietary data in a secure, governed, and scalable manner.  We are seeking individuals who have data engineering, data science, and insurance industry expertise to advance the integration of this platform into analytic solutions. These individuals will act as a liaisons between the analytics teams and the analytics platform team, reporting directly to the Chief Architect of the Data and Analytics platform, and with indirect reporting to the Analytics Lead of an assigned business unit. 

The role will combine hands-on work with strong communications and interpersonal skills.  Hands-on work will include building models, analyzing data, and managing data used for various analytic use cases.  Communication and interpersonal skills work will involve using your background in insurance to understand the problems being solved, and to coordinate work between the analytics platform and the data scientists. 
This role can be fully remote but will work eastern time zone business hours.

The successful candidate will ensure that

– the analytics teams understand and exercise the platform capabilities and associated best practices for efficient and effective use
– the analytics platform team understands business unit needs, translating their needs into new features and capabilities improving usability and value.

The blend of business-development, data, and quantitative skills makes this a unique opportunity.  This will also be a high-profile role, reporting directly to the Chief Architect of the Data and Analytics platform, and with “dotted line” reporting into the Analytics Lead of the assigned business unit. 

Responsibilities will include:

– Identifying projects that can be run in or transitioned to our cloud-based analytics platform
– Helping modeling teams implement their work in an AWS-based modeling environment using tools such as Python, R, and Databricks
– Identifying data sets and tools that exist in the analytics platform that can improve the quality and impact of work the insurance teams are doing.
– Identifying new data sets and tools that should be brought into the analytics platform to further improve the value our insurance analytics teams can create for customers
– Building models in a research setting, and then operating them in an operational setting.

Requirements

We are looking for candidates with a blend of data science, data engineering, and business experience in the insurance industry. 

– Degree in a quantitative discipline and 3-5 yrs experience in the insurance industry, or graduate degree and 1-3 yrs. experience in the insurance industry. 
– Comfortable working with Python, R, SQL queries, in Unix/Linux systems.  Experience with Databricks a strong plus. 
– Quantitative modeling experience, descriptive and predictive analytics.  This can include techniques such as linear regression, statistical modeling, and machine learning.
– Experience working in cloud computing. AWS preferable.
– Skill in developing automated processes, integrations of processes within systems, process improvement and system development for data and analytic pipelines.
– Critical thinking and action oriented, able to formulate plans to solve problems and explain the solution to others.  Able to motivate team members to work together.