Data Scientist

Job Description We are seeking a highly skilled Clinical NLP / AI Engineer to join our Data Science and NLP development team. In this role, you will analyze and process large-scale clinical and healthcare textual data using AI-powered NLP techniques and advanced machine learning models. You will contribute to building, improving, and scaling intelligent healthcare solutions by leveraging cutting-edge technologies, including large language models (LLMs) and agentic AI workflows. Key Responsibilities • Analyze, process, and extract insights from clinical and healthcare textual data using advanced NLP techniques • Design, develop, and enhance machine learning and deep learning models for healthcare applications • Leverage Large Language Models (LLMs) and tools such as LangGraph to build complex, agent-based AI workflows • Improve and optimize existing NLP workflows for performance, accuracy, and usability • Develop NLP modules using Python and other relevant programming or scripting languages • Perform data preprocessing, data quality assessments, and validation of NLP outputs • Create systematic testing frameworks, error-handling procedures, and technical/user documentation • Build and maintain ETL pipelines for structured and unstructured data from diverse data sources, including MCP servers • Work with Engineering teams to design scalable data infrastructure using SQL and AWS big data technologies such as EMR, Spark, and PySpark • Integrate and deploy generative AI solutions using AWS Bedrock • Collaborate cross-functionally with Data Engineering, Platform, and Clinical teams to deliver robust healthcare AI solutions Required Skills & Qualifications • Strong background in Data Science, Machine Learning, and NLP • Hands-on experience with Python for NLP and ML development • Experience working with clinical or healthcare text data (EHRs, clinical notes, reports, etc.) • Practical experience with LLMs and generative AI applications • Familiarity with LangGraph or similar agent-based AI orchestration frameworks • Experience building ETL pipelines using SQL and big data frameworks such as Spark / PySpark • Working knowledge of AWS services, particularly AWS Bedrock • Experience with relational databases such as PostgreSQL or MySQL • Understanding of data preprocessing, model evaluation, and validation techniques Preferred Qualifications • Experience in healthcare, life sciences, or clinical informatics domains • Knowledge of MLOps, model deployment, and monitoring in production environments • Familiarity with HIPAA-compliant systems and healthcare data privacy standards