Chief Data Officer – Insurance

We help the world see new possibilities and inspire change for better tomorrows. Our analytic solutions bridge content, data, and analytics to help business, people, and society become stronger, more resilient, and sustainable. Purpose of the Role

• Ensure a view of what is the optimal data content needed to support and enhance the business’s mission and objectives is developed and maintained
• Ensure our data content and platforming of data is continually advancing towards this optimal state
• Ensure the efficiency and effectiveness of our data management capabilities, processes, and community across the enterprise are world class and always improving
• Ensure data is generally moving in the direction of being more readily accessible and usable while adhering to the required governance and protection standards

Primary Goals to Be Assured by the Chief Data Officer

• Verisk has a conceptualized and modeled view of what the ideal content is to support analytics within the vertical (across all units in that vertical)
• Verisk has a data sourcing and data structuring plan to fully represent this conceptualized data model
• Verisk is operating on a world class tech stack to manage all data types in every way
• Verisk has a data engineering community that is right sized and appropriately skilled for the work needed
• Verisk has available a set of data engineering resources, residing in the center that

1) ensure methodological excellence across the enterprise, and 2) can offer resources to individual projects to ensure timely completion

• Verisk’s data capabilities and methods are world class and always improving
• Commercialization opportunities for data assets or providing data management services and IP to our clients are pursued with vigor

Specific Responsibilities of the Chief Data Officer 1. Verisk has a conceptualized and modeled view of what the ideal content is to support analytics within the vertical (across all units in that vertical)

• Develop and maintain a data model that contains the major entities and attributes which represent the ideal state of content and structure for the vertical. The model should account for both data in its raw state (as it was received from the source) and any transformed/normalized views that would create efficiencies and provide value added transformed attributes
• Update model as needed (but no less than every 12 months) to keep pace with the changing state of both data availability and the business
• Review this ideal state with the business and ensure their understanding of why it represents the ideal state for us to be in

2. Verisk has a data sourcing and data structuring plan to fully represent this conceptualized data model

• Develop and maintain a 12 month rolling plan to increasingly populate our data model so our conceptual model is fully realized over time
• Identify new or existing raw sources of information to better populate our conceptual data model
• Determine most effective means for ingesting data from its source and execute
• Define the data engineering and manipulation (if any) required to make the data most usable.

Specifically, what data will be left in its raw state and for data to be transformed into a more normalized state what the transformation rules are

• Provide the highest quality data to the user community by developing and adhering to a data validation process that identifies and corrects data issues at ingestion
• Update CEO and CIO quarterly on progress towards full population of the data environment

3. Verisk is operating on a world class tech stack to manage all data and data types in every way

• Publish and maintain a set of technical standards that will define the right tools and how they are to be deployed and used for purpose.

At the very least this should include:

• Data storage and repository tools that account for both structured and unstructured persistent data storage i.e., RDMS and file system techniques
• ETL tools required to manipulate data into new structures and formats
• Data exploratory tools
• Metadata and Master Data Management tools
• Data quality and reporting tools
• Develop a 12 month rolling plan to migrate data environments across Verisk to a more consistent state that adheres to these standards
• Update CEO and CIO quarterly on progress and adjustments to plan

4. Verisk has a data engineering community that is right sized and appropriately skilled for the work needed

• Maintain a current census of the data engineering community within the vertical
• Develop a minimum set of standards for skills required by a Verisk data engineer
• Continually assess the skill level and identify areas of concern/need and pursue proper path to address e.g., upskilling, transfer, retrain, new skills training, etc.
• Create a rotation process for acceleration of in-flight projects and career advancement
• Establish in partnership with the CHRO an ongoing program of recruitment for talent to be made available to business verticals as well as to populate the center’s…

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