Description

Position Overview

We are seeking a dynamic and innovative Data Scientist/AI Specialist to lead the development of cloud-based predictive models and AI-driven solutions that enhance early disease detection and streamline clinical workflows. This role bridges advanced analytics with real-world clinical applications across therapeutic areas such as oncology, neurology, and rare diseases.

Key Responsibilities

  • AI Model Development: Design and deploy cloud-native predictive models using imaging and clinical data to support early disease screening and reduce physician workload.
  • Clinical Trial Optimization: Drive initiatives in trial feasibility, site selection, and patient journey analytics to improve outcomes across multiple therapeutic domains.
  • Cross-Functional Collaboration: Partner with engineers, clinical scientists, and product teams to build scalable AI solutions and integrate them into enterprise platforms.
  • Generative AI Applications: Leverage large language models (e.g., GPT, Gemini, Claude) for automated document generation, biospecimen tracking, and protocol design using retrieval-augmented generation (RAG) and domain-specific ontologies.
  • Bioinformatics & Omics Analysis: Perform differential gene expression analysis using RNA-seq and proteomics data, employing statistical modeling and bioinformatics pipelines (e.g., Nextflow).
  • Workflow Automation: Develop and automate pipelines for assay development, clinical reporting, and AI-assisted decision-making tools.
  • Documentation & Reproducibility: Maintain robust documentation and ensure reproducibility of data science workflows using tools like Confluence and Jira.

Required Qualifications

  • 2–6+ years of experience in healthcare analytics, AI/ML, or life sciences consulting.
  • Proficiency in Python, R, JavaScript, and full-stack development (MERN stack).
  • Hands-on experience with cloud platforms (AWS, Azure, GCP, Databricks) and containerization (Docker).
  • Strong understanding of deep learning frameworks (TensorFlow, Keras) and backend APIs (FastAPI, Flask).

Preferred Skills

  • Experience with clinical imaging analytics (MRI, CT, histopathology).
  • Familiarity with genomic data analysis, gene enrichment techniques, and nonparametric statistical methods.
  • Exposure to AI applications in clinical documentation, biospecimen workflows, and disease taxonomy modeling.
  • Background in oncology, neonatal care, or neurodegenerative disease research is a strong plus.