Data Science - Senior Architect (Healthcare & Life Sciences)

Data Science Sr. / Lead / Architect – Healthcare & Life Sciences

Role Overview

· We are looking for an experienced Data Science Sr. / Lead / Architect to architect and deliver enterprise AI solutions across Commercial, R&D, and Sales & Marketing within Healthcare & Life Sciences.

· The role combines AI architecture, GenAI/Agentic AI engineering, technical leadership, client consulting, solutioning, and rapid prototyping.

Key Responsibilities

AI Architecture & Technical Leadership

· Architect scalable, secure, production-ready AI/ML solutions spanning data, models, LLMs, agents, applications, APIs, infrastructure, security, and observability.

· Lead and mentor Data Scientists and Senior Data Scientists, driving technical excellence, coding standards, and delivery practices.

Consulting & Solutioning

· Lead executive discovery with Sales, Account Management, Practice Leaders, and Delivery teams to understand client priorities, challenges, and transformation roadmaps.

· Drive proposals, presentations, solution architectures, demos, business cases, GTM assets, and thought leadership.

Generative AI & Agentic AI

· Design and implement RAG architectures across structured and unstructured data, including embeddings, vector search, retrieval, reranking, and context management.

· Design multi-agent systems using LangGraph, including memory, planning, reasoning, tool use, and autonomous task execution.

· Integrate LLM applications with enterprise data, APIs, and business systems.

ML Engineering & MLOps

· Design and operationalize end-to-end ML/AI pipelines with Data Engineering and MLOps teams, covering deployment, monitoring, versioning, evaluation, and lifecycle management.

· Rapidly build POCs, prototypes, and demos and translate them into measurable business value and ROI.

Required Qualifications & Experience

Experience

· 5–7+ years designing, building, and deploying AI/ML solutions.

· Experience in Pharmaceutical, Healthcare, or Life Sciences IT, including healthcare datasets such as EHR/EMR, claims, clinical, or imaging.

· Experience delivering production AI/ML solutions within quality, compliance, and regulated environments.

· Experience developing predictive models and/or digital twins.

Technical Skills

· Strong Python and SQL skills with understanding of data modelling, ETL/ELT, pipelines, and data warehousing.

· Strong knowledge of supervised, unsupervised, and deep learning using TensorFlow and/or PyTorch.

· Hands-on experience with LLMs, Generative AI, RAG, LangChain/LangGraph, prompt engineering, tool calling, structured outputs, guardrails, evaluation, and model selection.

· Experience integrating AI applications with enterprise data, APIs, and business systems.

· Understanding of AWS/cloud architecture, MLOps tools such as MLflow, Kubeflow, or SageMaker, and containerization, CI/CD, deployment, monitoring, and production operations.

· Strong communication, stakeholder management, and technical leadership skills.