AI Data Scientist

You will be joining our customer's team as an AI Data Scientist at micro1, where you will play a crucial role in driving advancements in digital healthcare and clinical trial optimization using AI, ML, and Generative AI technologies. Your primary responsibilities will include: - Designing, developing, and implementing AI/ML and GenAI solutions to optimize various aspects of clinical trial operations such as patient recruitment, retention, and real-time data monitoring. - Supporting the development of advanced GenAI applications to automate the generation of clinical trial documentation including medical reports, study protocols, and patient narratives. - Collaborating with stakeholders and subject matter experts to build digital healthcare tools that enhance data collection and patient engagement. - Engineering predictive and generative AI models using diverse healthcare datasets like EHRs, wearables, patient-reported outcomes, HEOR, and phase IV studies. - Applying natural language processing and large language models (LLMs) for medical text analysis and research interpretation in clinical applications. - Ensuring all AI/ML solutions comply with regulatory standards and data privacy requirements. - Leveraging cloud-based platforms, especially AWS, for scalable model deployment and following MLOps practices. Qualifications required for this role include: - Associate degree in Data Science, Computer Science, Biostatistics, or a related field. - 3-5 years of professional experience with at least 1 year of experience applying AI/ML techniques to healthcare or clinical research data. - Strong programming skills in Python, R, or similar, with hands-on expertise in modern ML frameworks like PyTorch and TensorFlow. - Proven experience working with generative AI technologies, including LLM architectures and frameworks. - Experience in designing and developing digital healthcare applications and tools. - Proficiency in written and verbal communication to effectively convey complex technical information. - Familiarity with cloud services, especially AWS, and best practices in version control and MLOps deployment. Preferred qualifications include experience in implementing AI/ML solutions within healthcare or clinical research environments, expertise in healthcare data integration and regulatory compliance, and knowledge of advanced digital healthcare tool design and patient engagement strategies.,