Cohere Health
Opportunity Overview As the Manager, Machine Learning & Data Science, you will play a key role in building and scaling Cohere Health’s AI capabilities in India. You’ll lead a team of machine learning engineers and data scientists focused on developing and deploying models that automate and augment complex clinical and administrative workflows. This team is responsible for the full lifecycle of applied machine learning and data science—from problem framing and experimentation to production model deployment and ongoing optimization. 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. What you’ll do: Lead, mentor, and develop a team of machine learning engineers and data scientists, fostering a collaborative, high-performance environment Act as a hands-on contributor across the ML/DS lifecycle, including data exploration, feature engineering, model development, evaluation, and deployment Design, develop, and deploy machine learning models for retrieval, classification, and generative use cases across structured and unstructured data Translate complex business and clinical problems into scalable machine learning and data science solutions Establish and uphold best practices for experimentation, model validation, performance tracking, and reproducibility Partner cross-functionally with Product, Engineering, Clinical, and Analytics teams to align solutions with business priorities Guide the development of scalable data science and machine learning systems, including data preprocessing pipelines and production workflows Monitor model performance, identify opportunities for improvement, and drive continuous iteration and optimization Communicate technical concepts, methodologies, and insights clearly to both technical and non-technical stakeholders Contribute to hiring and scaling the team in India, including recruiting, onboarding, and coaching team members ISMS roles and responsibilities: Good knowledge of Information security Oversee specific business processes within the ISMS. Responsible to manage the ISMS documentation, conduct risk assessments, and implement risk treatment plans. Risk Owners are responsible for identifying, assessing, and managing risks within their areas of responsibility. They are also responsible for implementing risk treatment plans. Conduct the BCP and other test related to information security continuity along with CISO Responsible for monitoring and reporting on the performance of the ISMS. Responsible for implementation of security policies and procedures and report any issues to the CISO. Required Qualifications:
Minimum 8+ years of experience in machine learning, data science, or applied AI roles, of those a minimum 2+ years of experience must be leading technical teams Strong hands-on experience building, evaluating, and deploying machine learning models in production Solid foundation in statistical methods, experimental design, and model evaluation Proficiency in Python and experience with ML frameworks (e.g., PyTorch, scikit-learn) Experience working with large, complex datasets (structured and/or unstructured) Strong problem-solving skills with the ability to translate business challenges into analytical solutions Excellent communication skills, with the ability to present complex concepts clearly to diverse stakeholders Experience working in fast-paced, evolving environments Nice-to-haves Experience in healthcare, particularly with payer, provider, or clinical data Experience with NLP, deep learning (e.g., transformers), or generative AI (e.g., RAG) Familiarity with MLOps practices and production ML systems Experience with Spark or large-scale data processing frameworks Exposure to cloud platforms (e.g., AWS, SageMaker) Experience working in a global or distributed team environment Prior experience in a GCC or building teams in India Interview Process*: Connect with Talent Acquisition Meet with the Hiring Manager Behavioral Interview(s) Case Study Interview with Senior Leadership *Subject to change About Cohere Health: Cohere Health’s clinical intelligence platform and agentic AI-powered solutions connect health plans’ strategic goals and providers’ needs, optimizing the speed, cost, and quality of care. With an enterprise approach that streamlines payer-provider decision-making across the care continuum–including policy, prior authorization, payment accuracy, and more–the company improves collaboration and reduces burden, resulting in up to 8x ROI and 94% provider satisfaction. With the acquisition of ZignaAI, we expanded our AI-native platform with a comprehensive Payment Integrity Suite that spans data mining, clinical and coding validation, authorization and claims reconciliation, and end-to-end payment integrity services across pre- and post-pay workflows. By connecting clinical and payment insights, our transparent, AI-powered solutions help health plans proactively improve payment accuracy, reduce waste and vendor dependency, strengthen provider relationships, and build smarter, more efficient payment integrity programs. Cohere Health’s innovations continue to receive industry-wide recognition. We’ve been recognized on TIME’s World Top HealthTech Companies 2025 list, the 2025 Inc. 5000 list, in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. We can’t wait to learn more about you and meet you at Cohere Health! Equal Opportunity Statement: Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all. To us, it’s personal.