Data Scientist, Clinical Research & AI Data Representation (Information Specialist)

Overview

*Job Overview Summary *

We are seeking a data-driven Information Specialist or Data Scientist to leverage advanced AI and data science to transform complex clinical and healthcare information into actionable insights. This role emphasizes developing analytical solutions and AI-assisted data representation techniques to enhance clinical study optimization and accelerate drug discovery. You will drive innovation, contributing to a product roadmap that utilizes scalable infrastructure.

*Key Responsibilities *

Clinical Data Analysis & Modelling: Design and implement ML/statistical models for clinical research data (RWE, EHR, omics, clinical trials).

AI-Assisted Information Visualization: Innovate AI-driven visualization for complex clinical data, ensuring clarity for medical and research stakeholders.

Prompt Engineering & Generative AI: Apply expertise in prompt engineering to guide and evaluate Generative AI/LLM applications for information extraction, summarization, and retrieval in clinical contexts.

Clinical Trial Data Strategy: Contribute to data science strategy, specifically aligning with clinical study optimization goals and regulatory requirements.

Cross-functional Collaboration: Partner with clinical, medical, and engineering teams to translate research questions and information needs into data solutions.

MLOps: Deploy, monitor, and maintain ML models in production, adhering to strict regulatory standards (GCP, HIPAA, GDPR).

*Qualifications *

Clinical & Healthcare Domain: Essential: Demonstrated hands-on experience and deep understanding of clinical research, life sciences, or healthcare data.

Education & Experience: Bachelor’s degree (4-year professional degree) in Data Science, Information Science, Bioinformatics, or a related quantitative field, OR a Master's degree in a relevant field. 3+ years of relevant experience

Programming & Tools: Proficiency in Python (Pandas, Scikit-learn, deep learning frameworks) and/or R, strong SQL skills.

Databricks & Big Data: Extensive, hands-on experience with the Databricks platform (Databricks SQL, Databricks ML, Delta Lake) and Spark (PySpark/Scala Spark) for large-scale data processing, ETL, and feature engineering.

Prompt Engineering: Demonstrated practical experience with prompt engineering, LLMs, or related conversational AI applications.

Analytical & Communication Skills: Excellent analytical, critical thinking, and problem-solving abilities. Strong communication and interpersonal skills to articulate complex clinical and AI concepts to both technical and medical teams.

Cloud Platforms: Experience with cloud-based platforms (AWS, Azure, GCP) for data storage, processing, and analytics is a plus.