Christopher Boyd

Christopher Boyd, MPA

Health Data Strategist @ Washington State Health Care Authority

A formal background in health policy, a penchant for data-driven decision-making, and a keen sense of what can be achieved with the right technology.

Expertise includes building Agile engineering teams, establishing architectural principles, streamlining data pipeline operations, and driving initiatives that enable better decision-making through robust data systems.

Key Skills

IT Strategy

Developing and implementing enterprise-wide data strategies and value metrics frameworks.

Cloud Computing

Establishing cloud-native data architectures (AWS, Azure) and streamlining data pipeline operations.

Team Management

Fostering Agile environments and managing cross-functional teams of engineers and analysts.

Programming Languages & Tools

Python R SQL Git GIS

Professional Narrative

I’ve enjoyed my role as a leader, and I’ve actively invested in it with agency sponsored training. I believe I’m well suited to take on the role overseeing both the business and technical units due to the relationships I’ve built since joining this team, and my unique combination of education and technical experience.

I’m a Masters graduate from the Evans School of Public Policy and Governance at UW, where I specialized in the area of health policy. My academic training includes policy analysis, management, accounting, and extensive writing. I’ve used this training to inform programmatic choices in health care delivery, as well as outcomes evaluations, throughout my career. Since graduating from the Evans School, I’ve worked primarily in data warehousing, and acquired many of the skills from the broad field of data science.

At the start of my career, I helped to establish a clinical data warehouse for one of the largest ObGyn practices in the country, and I later established a team of analysts who were responsible for the ongoing development of that warehouse. I played the role of business analyst to interpret the requirements of a clinician director into concrete technical objectives. I provided the results of my team’s analysis in written reports, interactive dashboards, and in-person to audiences of up to 100 people.

I worked with big data as an analyst for WebMD, querying the claims records of 70 million individuals. As the Lead Data Engineer for the EDW project, I’ve developed and trained my team on a code promotion process driven by version control, a set of in-house Python tools developed to support the EDW data pipeline, and a robust “infrastructure as code” platform based on the AWS CloudFormation tool.

I look forward to discussing this position, and the future of the team, in more detail.