Senior Director I, Modeling Data Pipelines

Leads the development and delivery of end-to-end data pipelines and feature store capabilities that give data scientists the modeling data they need, at the speed the P&L vertical teams require.

Provides strategic and tactical direction for the department, and helps set the direction for how MDS, data scientists, and deployment teams across US Date Science (USDS) work with modeling data. This position requires a proven ability to lead large-scale change across multiple teams.

Responsible for the management, technical oversight, and development of a team of data analysts, MLOps specialists, and subject matter experts. Owns the strategy and execution for modernizing and standardizing the modeling data lifecycle, from data ingestion through model deployment, in partnership with our P&L vertical data science, modeling data, and deployment teams.

Uses modern pipeline frameworks and scalable architecture patterns so data lineage is tracked throughout feature development. Leads the design and adoption of a feature store strategy that ensures features are defined once, managed consistently across model development, calibration, and deployment, and can be added to directly by data scientists. Leverages pipeline modernization to develop AI solutions that speed up how features are built, tested, and maintained.

Requires deep knowledge of modern data pipelines and feature management practices, including tools such as dbt, Snowflake, and Databricks, and advanced application of those practices to the development, calibration, and deployment of pricing models.

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

• Advanced degree in Statistics, Mathematics, Data Science, Computer Science, or a related field preferred.
• Typically 8+ years of relevant experience, including leadership experience in data science, analytics, data operations, or MLOps.
• Experience sourcing, integrating, and governing data from enterprise data warehouses and external vendors
• Ability to partner with data science, technology, and business stakeholders and communicate clearly with technical and non-technical audiences
• Responsible for the management, technical oversight and development a team of data science and advanced analytics staff, which may include subordinate managers.
• Coaches team to understanding of organizational vision and goals.
• Collaborates with business partners to develop tools and services such as modeling, dashboard development, and decision aids to drive strategic decision making.
• Provides strategic and tactical direction at the highest levels. Has accountability for the performance and results of one or more large, strategically important business unit in an extremely large market.
• Works on issues of diverse scope where analysis of situation or data requires evaluation of a variety of factors, including an understanding of current business trends.
• Owns relationship with a defined segment of the business, delivering advanced tools and insights, including ongoing monitoring of metrics and initiatives.
• Responsible for highly technical, individualized and difficult to develop tools and their usage which are transformative in nature and have broad strategic impact to the aligned business units(s).
• Leads highly technical, complex, and cross functional projects that drive change across function, SBU or Corporate Department.
• Directs and may perform highly complex, technical and creative predictive analytics projects and cross functional assignments within designated business unit collaborating with multiple functions.
• Shapes the data science community and/or larger audiences and leads cross functional working groups.