Data Scientist - Clinical Trial Analytics

Role Overview

We are seeking a Data Scientist with strong expertise in clinical trial analytics to support feasibility analysis and site selection initiatives. The ideal candidate will combine data science, AI/ML, and agent-based automation capabilitiesto develop predictive models and intelligent workflows that enhance clinical trial planning and operational decision-making.

Key Responsibilities

• Develop and implement analytics models and AI-driven solutions to support clinical trial feasibility and site selection.
• Build predictive models and decision-support tools leveraging clinical trial operational data.
• Design and implement AI agent-based workflows and automation frameworks to improve data analysis and operational insights.
• Work closely with clinical operations, data management, and trial teams to translate analytical insights into actionable strategies.
• Develop and optimize data pipelines and analytical models using Python and SQL.
• Deploy scalable analytics solutions using modern AI/ML frameworks and cloud-based platforms.

Required Skills & Experience

• 5+ years of experience in data science or analytics within clinical trial operations.
• Strong experience with clinical trial feasibility analytics and site selection methodologies.
• Proficiency in Python and SQL for data processing, modeling, and analytics.
• Hands-on experience with AI/ML frameworks and predictive modeling techniques.
• Experience developing AI agents, workflow automation solutions, or intelligent analytics systems.
• Prior experience working in a CRO, pharmaceutical, or clinical research environment.
• Strong communication and stakeholder collaboration skills with clinical and cross-functional teams.

Preferred / Nice-to-Have Skills

• Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG) pipelines.
• Exposure to multi-agent systems and AI orchestration frameworks.
• Familiarity with cloud platforms (AWS, Azure, or GCP).
• Experience with containerized deployment (Docker, Kubernetes).