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.

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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

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

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

Generative AI & Agentic AI

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

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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

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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

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

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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

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

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

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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.