Principal Data Scientist

Job Responsibilities

• Collaborate with cross functional units to understand business needs and gather insights to support internal data science tool development.
• Develop and validate data science tools for clinical research, and trial optimization.
• Ensure the scalability, maintainability, and reliability of analytical solutions through software engineering best practices (e.g., testing, documentation, CI/CD pipeline).
• Design, build and implement scalable, secure and efficient infrastructure on AWS.
• Communicate technical results and insights to stakeholders through clear, structured presentations and documentation.

Qualifications

• Bachelor’s degree in computer science, Data Science, Statistics, Mathematics, or a related field. Minimum of 12 years of Data Science experience with a Bachelor’s degree, 10 years with a Master’s, or 6 years with a Ph.D., including at least 5 years of hands-on experience developing production-grade software in programming languages such as Python or R.
• Demonstrated understanding of software architecture, performance optimization and validation.
• Strong expertise in Machine Learning and Deep Learning techniques (e.g., Scikit-learn, TensorFlow, or PyTorch).
• Demonstrated experience deploying and maintaining models in production (e.g., APIs, batch jobs, microservices).
• Strong analytical thinking and problem-solving skills.
• Experienced with Github.

Preferred Qualifications

• Master’s or Ph.D degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
• Demonstrated expertise in developing and optimizing scalable data architectures and analytics pipelines within cloud environments (AWS, GCP, or Azure), including experience with containerization (e.g., Docker).
• Experience with creating Large Language Models (LLMs) and GenAI based solution in production environment.
• Experienced in designing and implementing CI/CD pipelines.