Senior Data Scientist - Pharmaceutical Domain

Overview

We seek a seasoned Python developer specializing in Machine Learning and Artificial Intelligence, with a strong command of Deep Learning, NLP, and Generative AI technologies. The role involves crafting, refining, and deploying AI and ML solutions tailored to complex challenges within the pharmaceutical and life sciences sectors, including areas like healthcare, clinical research, drug discovery, pharmacovigilance, and medical data analysis.

Primary Duties

• Create, develop, and implement Machine Learning and Deep Learning models using Python programming.
• Devise NLP-based systems to manage and analyze both structured and unstructured textual information.
• Construct and deploy enterprise-level applications leveraging Generative AI and Large Language Models (LLMs).
• Conduct data preprocessing, feature engineering, model creation, rigorous validation, and optimization activities.
• Build scalable AI/ML pipelines and seamlessly integrate models into live production environments.
• Engage with LLMs including prompt engineering, manage embeddings, operate vector databases, and implement Retrieval-Augmented Generation (RAG) techniques.
• Assess and fine-tune AI/ML models based on specific business objectives and technical criteria.
• Develop solutions addressing text classification, information extraction, semantic search, document intelligence, summarization, and related NLP applications.
• Collaborate effectively with cross-functional teams including Data Engineers, Software Developers, Product Managers, and domain specialists to deliver robust AI products.
• Monitor and improve model performance continually, enhancing accuracy, reliability, scalability, and operational efficiency.
• Adhere to industry best practices encompassing model development, testing, deployment, documentation, and version control.
• Remain updated on new developments and innovations in Generative AI, LLMs, NLP, and broader AI/ML fields.

Essential Technical Qualifications

• Proficiency in Python with substantial practical experience.
• Deep comprehension of Machine Learning algorithms and their applications.
• Advanced skill set in Deep Learning methodologies.
• In-depth knowledge and hands-on experience with Natural Language Processing.
• Expertise working with Generative AI and Large Language Models.
• Familiarity with prominent ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Strong capabilities in data preparation, model training, evaluation, and enhancement.
• Understanding of AI/ML deployment processes and production system integration.

Preferred Experience in Generative AI

• Hands-on exposure to LLM platforms including OpenAI, Gemini, Claude, Llama, or equivalents.
• Experience implementing Retrieval-Augmented Generation (RAG) architectures.
• Skill in prompt engineering and thorough evaluation of LLMs.
• Knowledge of embeddings and usage of vector databases.
• Familiarity with frameworks like LangChain, LangGraph, or LlamaIndex.
• Proven experience designing AI-driven applications, including copilots, chatbots, or intelligent automation tools.