Collaborate with business to design, develop, and deploy advanced data science and AI solutions leveraging machine learning, large language models (LLMs), and modern data platforms.
Responsibilities
Collaborate with business to design, develop, and deploy advanced data science and AI solutions leveraging machine learning, large language models (LLMs), and modern data platforms.
Work with large-scale structured and unstructured datasets including clinical data, publications, real-world evidence, and other healthcare datasets.
Build predictive models and advanced analytics solutions to generate actionable insights and support data-driven decision making.
Develop LLM-powered applications such as AI assistants, knowledge-grounded reasoning systems, and Retrieval-Augmented Generation (RAG) pipelines.
Develop and maintain semantic layers, ontologies, and contextual data frameworks that enable consistent interpretation of data across AI systems and analytics workflows.
Requirements
Btech/Masters in a relevant fields such as Data Science, Statistics, Computer Science or a related discipline
Nice to have: AI techniques in healthcare, life sciences, or biopharma domains
Nice to have: Clinical data familiarity
Nice to have: Healthcare datasets familiarity
Nice to have: Real-world evidence sources familiarity
Collaborate with business to design, develop, and deploy advanced data science and AI solutions leveraging machine learning, large language models (LLMs), and modern data platforms.
Work with large-scale structured and unstructured datasets including clinical data, publications, real-world evidence, and other healthcare datasets.
Build predictive models and advanced analytics solutions to generate actionable insights and support data-driven decision making.
Develop LLM-powered applications such as AI assistants, knowledge-grounded reasoning systems, and Retrieval-Augmented Generation (RAG) pipelines.
Develop and maintain semantic layers, ontologies, and contextual data frameworks that enable consistent interpretation of data across AI systems and analytics workflows.
Requirements
Btech/Masters in a relevant fields such as Data Science, Statistics, Computer Science or a related discipline
Nice to have: experience applying data science or AI techniques in healthcare, life sciences, or biopharma domains
Nice to have: familiarity with clinical data, healthcare datasets, or real-world evidence sources
Nice to have: understanding of the pharma ecosystem and healthcare data sources
