Chief Data Scientist; Remote

TRIMEDX is an industry-leading, independent clinical asset management company delivering comprehensive clinical engineering services, clinical asset informatics, and medical device cybersecurity solutions to many of the largest health systems in the US. We help healthcare providers transform their clinical assets into strategic tools, driving reductions in operational expenses, optimizing clinical asset capital purchasing decisions and usage, improving caregiver satisfaction and productivity, maximizing resources for patient care, and delivering improved patient safety and protection.

TRIMEDX was built by providers, for providers, and leverages a history of expert clinical engineering with data on 90-95% of in-use medical equipment in the United States and an industry-leading data set of more than 6 million medical device records. A recent study by Fortune states that the global healthcare asset management market is estimated to be $215B by 2032 with a CAGR of 25.3%.

We are looking for the Chief Data Scientist who can accelerate our growth as a thought leader in Data Science, Research, and the application of models to solve complex business problems. This person will lead the Company’s efforts to create a data science practice dedicated to harnessing this proprietary data set to support commercialization of novel market solutions to enable providers to make informed decisions regarding their clinical asset investments and utilization.

This role will be one of the most prominent voices in the global medical device industry. As the Chief Data Scientist, you will be responsible for leading TRIMEDX data and AI architecture and design to help our customers increase their clinical asset utilization and reduce cost to operate. You will design our enterprise-wide AI and Machine Learning initiatives.

This new role will be instrumental in shaping and implementing our AI roadmap, driving innovation through advanced data modeling, and applying automation to optimize operations across diverse data ecosystems. It involves orchestrating Agentic AI across multiple SaaS infrastructures, including, but not limited to, Snowflake, Azure, Service Now, and Looker. In this role, you will work with senior executives and customers to arrive at solutions that significantly lift their business and accelerate growth.

You are a strategic leader with experience defining enterprise AI/ML platforms, focusing on LLMs, generative AI, and predictive modeling. You will implement model-driven features from concept to production, covering model creation, evaluation, performance metrics, A/B testing, drift monitoring, and self-correction with feedback loops. You will coach and train engineers in their career growth and set an example for the data and AI organization.

Your experience includes building pricing models, forecasting, and smart work assignment. You will stay at the forefront of AI/ML research and emerging technologies, evaluating and integrating cutting-edge tools and frameworks. You will foster a culture of experimentation and continuous learning within the data science team and create high levels of engagement across teams in partnership with other key leaders within broader teams.

• Minimum of 12 years of experience in computer science, data science, statistics or related field. Experience preference in machine learning, data analytics or related disciplines with a focus on algorithmic product development.
• Deep expertise in statistics, econometrics, predictive analytics, and related disciplines.
• Working experience with modeling tools and languages such as Python, PyTorch, JAX, Tensor Flow, SQL, and experience deploying production models on cloud platforms (AWS, Azure, GCP).
• Demonstrated experience leading data-driven initiatives; experience leading people is preferred.
• Demonstrated experience with multi-modal LLMs. Experience with A/B testing and co-creating MLOps practices for systemic application and maintenance of the models.
• Hands-on experience deploying high-impact, high-throughput, highly scalable, multi-modal ML models in Azure.
• Experience in data analysis using different types…