Vice President, Data Strategy - Trella Health

At Trella Health, our mission is simple: empowering meaningful change in healthcare.

We are building AI-enabled intelligence and workflows that help healthcare organizations make smarter decisions, strengthen operations, and support healthier outcomes for patients. Our platform connects health systems and post-acute providers through actionable intelligence and connected workflows that improve how care is coordinated across the healthcare continuum.

That work starts with our people. Trellavators are collaborative, curious, and committed to doing meaningful work that makes a measurable impact. We move quickly, support each other, keep our commitments, and continuously look for better ways to serve our customers and one another.

If you are excited by the opportunity to grow your career while helping shape the future of healthcare intelligence, workflows, and outcomes, we would love to meet you.

Position Overview:

We are seeking a visionary Vice President of Data Strategy to lead our enterprise data strategy and accelerate our growth as an AI-first healthcare organization. This executive will own the end-to-end data lifecycle—from infrastructure and governance to advanced analytics, machine learning, and generative AI—and translate that foundation into measurable clinical, operational, and financial outcomes.

The ideal candidate is equal parts strategist, technologist, and builder: someone who has scaled modern data platforms, deployed production AI systems, and navigated the unique complexity of healthcare data. You will partner with product, engineering, clinical, and commercial leadership to ensure data and AI are competitive differentiators, not back-office functions.

Location: This is a hybrid role with 1 day a week in our Atlanta or Philadelphia office.

Reports to: Chief Technology Officer

As the VP of Data Strategy at Trella, you will lead:

Strategy & Vision

• Define and execute a multi-year data and AI roadmap aligned to our enterprise strategy with clear investment cases, KPIs, and ROI milestones.
• Champion an AI-first operating model: embedding machine learning, predictive analytics, and generative AI into products, workflows, and decision-making across the organization.
• Serve as the executive voice of data, educating senior leadership, and customers on emerging AI capabilities and responsible adoption.

AI & Machine Learning

• Build and scale the organization’s AI/ML capabilities, including traditional ML, deep learning, NLP on clinical text, and generative AI / LLM applications (RAG, agentic workflows, fine-tuning).
• Establish MLOps and LLMOps practices covering model development, evaluation, deployment, monitoring, and retraining at production scale.