Manager, Data Operations

Owns the strategy and delivery of the training and calibration data the P&L vertical teams in US Data Science (USDS) and Product Delivery need for pricing. Leads the modernization of the department’s data architecture to keep pace with the organization’s growing needs.

Provides strategic and tactical direction for the department. This position requires deep knowledge of feature engineering and dataset preparation for data science, data architecture, and modern pipeline approaches, along with the proven ability to lead a large organization.

Leads and develops the teams within the Modeling Data Solutions (MDS) department. Oversees the sourcing of data from enterprise data warehouses and external vendors, including vendor data acquired to test potential new modeling features. Owns the process changes needed when new source systems come online, such as new policy or claims platforms. Directs the end-to-end pipelines team in modernizing existing MDS pipelines so that model-ready data can be delivered at the speed the P&L vertical teams need. Works closely with the Data Office and DAE to help shape the enterprise data strategy.

Oversees teams that serve as the data experts for their lines of business, explaining where the data comes from and how it was built, and working closely with data science partners on changes and improvements to the datasets.

Collaborates with USDS, ED&DS, Data Office, DAE, and Product Delivery in developing these solutions.

• 15+ years coding experience in data strategy, analytics, data management, data warehousing, data architecture, data product ownership or unstructured data environments, and defining and executing data governance policies and procedures
• Bachelor`s degree or equivalent experience required, MBA or advanced degree preferred
• Experience working in a global, multicultural environment working across multiple geographies and business groups
• Experience influencing senor level management and key stakeholders
• Strong written and oral communication skills required
• Familiarity with Agile practices
• Familiarity with process management a plus
• Working knowledge of cloud data platforms such as Snowflake and Databricks, and of AWS services including SageMaker
• Experience sourcing, integrating, and governing data from enterprise data warehouses and external vendors
• Strong understanding of data architecture, data pipelines, and data lineage practices
• Ability to partner with data science, technology, and business stakeholders and communicate clearly with technical and non-technical audiences
• Familiarity with modern pipeline and orchestration tools such as dbt and Airflow