Manager, Data Science

Data Science Manager

This leader will manage data scientists, oversee project delivery, partner with cross-functional teams, and shape the development of innovative AI/ML solutions.

• Lead and manage a team of data scientists, providing technical guidance, mentorship, and performance oversight.


• Own end-to-end delivery of data science and GenAI engagements for pharma/biotech clients.


• Translate business problems into analytical frameworks and ensure high-quality, timely project execution.


• Drive adoption of AI/ML capabilities across client engagements and internal initiatives.

• Architect, design, and review ML, statistical, and GenAI solutions, ensuring scalability, accuracy, and alignment with business objectives.


• Oversee the development, validation, and deployment of predictive models, NLP pipelines, and GenAI-based applications (e.g., summarization, insights automation, generative workflows).


• Lead cloud-based solution deployment (AWS, Azure, or GCP) including orchestration, MLOps best practices, and integration with enterprise systems.


• Ensure adherence to model governance, compliance, and responsible AI frameworks.

• 7+ years of experience

  in data science or advanced analytics roles, with at least

  2-3 years in a leadership or managerial capacity

  .


• Good to have prior experience in

  pharmaceutical, biotech, or healthcare consulting

  is mandatory.


• Strong expertise in

  machine learning, NLP, deep learning

  , and

  GenAI

  (LLMs, prompt engineering, RAG, fine-tuning, embeddings).


• Hands-on experience with cloud platforms such as

  AWS, Azure, or GCP

  ; exposure to

  MLOps

  frameworks preferred.


• Proficiency in Python, SQL, and common DS/ML libraries (TensorFlow, PyTorch, scikit-learn, Hugging Face, LangChain, etc.).


• Proven experience managing teams, delivering client projects, and presenting to senior stakeholders.


• Good to have understanding of pharma datasets (claims, RWE, clinical, medical insights, social data) and key use cases.


• Experience building GenAI solutions in production environments