I help clinicians, public health professionals and researchers turn their domain expertise into careers in healthcare data science, analytics and health AI.

I’m Director of Data Science at ADLM (Association for Diagnostics & Laboratory Medicine), where I lead data science programming, including our annual symposium, data challenges and education initiatives. I’m also a DrPH student at Johns Hopkins Bloomberg School of Public Health, researching algorithmic bias and patient safety in healthcare AI.

My path wasn’t linear. I’ve worked across federal health (an FDA fellowship and HRSA), consulting (Accenture Federal Services) and a national professional association. Along the way I learned how to translate between clinical, technical and regulatory worlds, which is the skill that most often gets people hired into these roles.

I can help you:

Position your clinical or research background for US healthcare analytics, informatics and AI roles
Rewrite your resume and LinkedIn so recruiters see a data professional, not just a clinician or academic
Map the landscape: health systems, payers, health tech, federal and nonprofit roles, and what each one looks for
Build a portfolio and a skills plan in Python, R and SQL that matches real job requirements
Prepare for interviews, including telling your impact stories clearly and confidently
Understand health AI governance, regulation and bias evaluation if you want to work in responsible AI

Who I work best with: physicians, nurses, lab professionals, epidemiologists and PhD or DrPH students who want structure, honest feedback and a concrete plan. I’ve worked with international professionals navigating the US market too.

Send me a message about where you are and where you want to go. I’m happy to tell you honestly whether I’m the right fit.