Senior Manager, Applied Science
About the role
thenwith that overview. What You'll Do: responsibilities. Use
Responsibilities
then- each bullet.
What You'll Need: Must-haves and Nice-to-haves. Could split into Requirements (must-haves) and Qualifications (nice-to-haves) or Skills. The instruction: Use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide mapping.
We have Must-haves (experience, education) and Nice-to-haves (domain experience). Could treat Must-haves as Requirements, Nice-to-haves as Qualifications or Skills. Also we have specific skills: Python, ML frameworks, AWS, statistical methods, etc. Those could go under Skills.
Pay & Perks: includes remote, travel %, benefits list, salary range. So we can have Benefits (list of benefits), Pay (salary range), Schedule (remote + travel %). The posting says "Fully remote opportunity with about 15% travel". That's schedule info.
Thus sections:
- About the role (overview)
- Responsibilities (What You'll Do)
- Requirements (Must-haves)
- Qualifications (Nice-to-haves) maybe.
- Skills (technical proficiencies: Python, ML frameworks, AWS, statistical methods, experimental design, etc.)
- Benefits (list: medical, dental, vision, life, disability, EAP, 401K match, FSA/HSA, Flex Time Off + holidays, up to 14 weeks parental leave, pet insurance)
- Pay (salary range $225k-$240k)
- Schedule (Fully remote with about 15% travel)
We must not include sections with filler like "commensurate with experience". Not present.
We must not include duplicated lines. Ensure we preserve all substantive info.
We need to output only HTML fragment, no or . Use
for headings. Use
- for lists. Use
for prose. We must not include markdown fences. Let's extract details. About the role: from "Opportunity Overview 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. This is a remote-first role that may require travel to Boston, MA for new hire onboarding and occasional in-person team meetings and company events." We could keep that as prose. Responsibilities bullets from "What You'll Do": - 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 Note there is an exclamation after impact; keep. Requirements (Must-haves): - 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 - Experience 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 Qualifications (Nice-to-haves): - Experience in transactional healthcare (e.g., Utilization Management, Payment Integrity, Risk Adjustment, Quality, Care Management, etc) - Experience driving process automation in a healthcare setting using modern language models - Experience applying retrieval and relational extraction techniques to unstructured clinical notes and other patient history documentation Skills: Could be overlapping with requirements; but we can separate technical skills: Python, ML frameworks (PyTorch, scikit-learn), AWS, statistical methods, experimental design, model evaluation, LLMs, classical ML. However we already have those in requirements. To avoid duplication, maybe we put Skills as a summary of technical proficiencies: Python, ML frameworks (PyTorch, scikit-learn), AWS, LLMs, classical ML, statistical methods, experimental design, model evaluation. But that duplicates content. The instruction says preserve ALL substantive information; do not invent or summarize away detail. If we put them in both Requirements and Skills, that's duplication. Better to assign each piece to only one section. So we could put Requirements as education/experience leadership, Nice-to-haves as domain experience, and Skills as technical proficiencies (Python, ML frameworks, AWS, LLMs, classical ML, statistical methods, experimental design, model evaluation). But then we lose some details like "experience leveraging both modern language models and classical ML techniques in a production setting" which is a skill. Also "Expertise in statistical methods, experimental design, and model evaluation" is skill. "Proficiency in Python and experience with ML frameworks (e.g., PyTorch, scikit-learn)" skill. "AWS experience" skill. "Demonstrated track record of driving decision making..." is more about ability, could be requirement. Thus we can allocate: Requirements: education/experience leadership (PhD/MS + years + 2+ years leading teams) and demonstrated track record of driving decision making (collaborating with business functions...). That's two items. Skills: technical proficiencies: experience leveraging LLMs and classical ML in production, expertise in statistical methods, experimental design, model evaluation, proficiency in Python and ML frameworks (PyTorch, scikit-learn), AWS experience. Qualifications (Nice-to-haves): domain healthcare experience items. Check if any other info: "Experience driving process automation in a healthcare setting using modern language models" and "Experience applying retrieval and relational extraction techniques to unstructured clinical notes and other patient history documentation" are nice-to-haves. Now Benefits: list: - Medical, dental, vision, life, disability insurance, and Employee Assistance Program - 401K retirement plan with company match; flexible spending and health savings account - Flex Time Off + company holidays - Up to 14 weeks of paid parental leave - Pet insurance Pay: salary range $225,000 to $240,000 annually; also mention total benefits package includes health insurance, 401k and bonus. But we already have benefits; we can keep Pay as salary range. Schedule: Fully remote opportunity with about 15% travel; may require travel to Boston, MA for new hire onboarding and occasional in-person team meetings and company events. That's schedule. Now produce HTML. We need to ensure we don't include any boilerplate like Equal Opportunity Statement, Interview Process, About Cohere Health, etc. Remove those. Thus final HTML:
About the role
...
Responsibilities
- ... ...
Requirements
- 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
- 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
Skills
- Experience 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
Qualifications
- Experience in transactional healthcare (e.g., Utilization Management, Payment Integrity, Risk Adjustment, Quality, Care Management, etc)
- Experience driving process automation in a healthcare setting using modern language models
- Experience applying retrieval and relational extraction techniques to unstructured clinical notes and other patient history documentation
Benefits
- Medical, dental, vision, life, disability insurance, and Employee Assistance Program
- 401K retirement plan with company match; flexible spending and health savings account
- Flex Time Off + company holidays
- Up to 14 weeks of paid parental leave
- Pet insurance
Pay
The salary range for this position is $225,000 to $240,000 annually.
Schedule
Fully remote opportunity with about 15% travel; may require travel to Boston, MA for new hire onboarding and occasional in-person team meetings and company events.
Check for any missing substantive info: The overview also mentions "This is a remote-first role that may require travel to Boston, MA for new hire onboarding and occasional in-person team meetings and company events." That's in schedule. Also overview mentions "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." That's covered in responsibilities? Not exactly; we have responsibilities list includes lead/mentor/develop team, translate problems, validate solutions, partner with AI Engineering, partner cross-functionally, communicate technical concepts, contribute to recruiting. The "establish best practices" and "hands-on technical contributions" maybe missing. Could add a responsibility bullet: "Combine hands-on technical contributions with team leadership to establish best practices and drive high-impact solutions". But we must not invent; we need to preserve that detail. The overview includes that sentence. We should incorporate it as a responsibility bullet. Thus add to responsibilities: "Combine hands-on technical contributions with team leadership to establish best practices and drive high-impact solutions in close partnership with Product, Engineering, Clinical, and Analytics stakeholders." Also overview: "This is an opportunity to shape both the technical direction and team culture within a growing global organization." Could be a responsibility or about role
- for lists. Use