Senior Manager of Applied Science, Cohere Health

• PhD with 7+ years experience or MS with 10+ years experience in machine learning, data science, or applied AI roles, of those a minimum 2+ years of experience leading and managing technical teams
• Experiencing leveraging both modern language models (agentic or non-agentic LLM) and classical ML techniques in a production setting
• Expertise in statistical methods, experimental design, and model evaluation
• Proficiency in Python and experience with ML frameworks (e.g., PyTorch, scikit-learn)
• AWS experience
• Demonstrated track record of driving decision making by collaborating with business functions and product to accurately determine problem statements, form falsifiable hypotheses, and apply robust experimentation and analyses to drive toward valuable and robust solutions

Desirable

• As the Sr. Manager, Applied Science, you will play a key role in building and scaling Cohere Health's AI capabilities. You'll lead a team of Applied Scientists focused on developing, evaluating, and deploying models that automate and augment complex clinical and administrative workflows
• This team is responsible for the full lifecycle of applied machine learning from problem framing, rigorous attention to methods and experimentation, to partnering with AI Engineering to deploy and monitor models. You'll work with structured and unstructured healthcare data to generate insights and power intelligent systems that improve prior authorization and broader clinical decision-making
• As a player-coach, you'll combine hands-on technical contributions with team leadership, helping to establish best practices, mentor team members, and drive high-impact solutions in close partnership with Product, Engineering, Clinical, and Analytics stakeholders. This is an opportunity to shape both the technical direction and team culture within a growing global organization
• Lead, mentor, and develop a team of Applied Scientists, fostering a collaborative, high-performance environment
• Translate complex healthcare business and clinical problems into scalable machine learning and data science solutions
• Validate those solutions with methodological and statistical rigor to assure that our Clinical AI is reliable, reproducible, and safe
• Partner with AI Engineering to scale those solutions to create real healthcare impact!
• Partner cross-functionally with Clinical Operations, Product, Engineering, and platform teams to align technical research and validation work with business priorities
• Communicate technical concepts, methodologies, and insights clearly to both technical and non-technical stakeholders
• Contribute to recruiting, onboarding, and developing team members

• Connect with Talent Acquisition for a Preliminary Phone Screening
• Meet your Hiring Manager!
• Behavioral Interview(s)
• Case Study