At IMO Health, a core team of software developers, data scientists, and domain experts combines computer science and healthcare expertise to help professionals access high-quality health information quickly and easily. We need a Senior Data Scientist with a strong background in building and maintaining AI-driven web applications to join this team! In this role, you will design, develop, and optimize machine learning models for real-world healthcare applications. You will work with large, complex datasets, apply cutting-edge machine learning and natural language processing (NLP) techniques, and collaborate with cross-functional teams to integrate AI solutions into our products. A successful candidate will have experience in end-to-end machine learning model development, from data preprocessing and feature engineering to model training, evaluation, and deployment in production environments. You should be comfortable with cloud-based AI infrastructure, scalable ML pipelines, and best practices in MLOps. Join our growing Data Science & Analytics department as a Senior Data Scientist to help drive AI-powered innovation in healthcare!
WHAT YOU'LL DO:
Leverage machine learning, deep learning, prompt engineering and data mining techniques to develop Clinical AI solutions.
Develop knowledge graphs and structured data representations to enhance AI-powered insights and decision-making.
Conduct healthcare research by applying machine learning, deep learning, prompt engineering, data mining and AI techniques.
Implement advanced statistical, predictive modeling, and deep learning techniques, ensuring interpretability and scalability.
Develop and maintain ML pipelines, integrating multiple data sources, including warehoused and pre-modeled data.
Interpret and communicate insights and findings through reports, dashboards, and presentations for internal and external audiences.
Support organizational decisions with well-validated models, algorithms, and data-driven recommendations.
Follow software engineering best practices to write clean, reliable, and testable code, supporting rapid delivery via CI/CD and automated deployments.
Work closely with Product Owners and cross-functional teams to align AI/ML solutions with business needs.
Estimate technical work for product requests, assisting in roadmap planning and prioritization.
Champion adherence to technical standards and ensure alignment with architectural direction.
Identify, track, and minimize technical debt within the team.
Lead and coordinate incident resolution, root cause analysis, and preventive action implementation.
Collaborate with architects to explore new technologies, proof-of-concepts (PoCs), and technical roadmaps.
Mentor team members, fostering technical growth and skill development in machine learning, NLP, and AI research.
Proactively anticipate challenges and implement creative, out-of-the-box solutions to technical problems.
Foster a culture of continuous learning, staying up to date on data science, ML, AI, and analytics tools, techniques, and industry best practices.
WHAT YOU'LL NEED:
Master’s degree in Statistics, Data Science, Computer Science, or a related field; PhD preferred.
Strong foundation in data science, machine learning, deep learning, and AI principles.
Advanced knowledge of statistical techniques, probability, multivariate calculus, and linear algebra.
Demonstrated experience building, fine-tuning, and deploying machine learning models, including large language models (LLMs), NLP models, and predictive analytics solutions.
Experience in prompt engineering, Langchain, Agentic AI and transfer learning techniques for LLMs.
Hands-on experience with deep learning frameworks such as TensorFlow, or PyTorch.
Experience implementing knowledge graphs and structured data models for AI-driven applications.
Expertise in model versioning, monitoring, A/B testing, and deployment in production environments.
Strong experience with Python for machine learning, data processing, and full-stack development.
Hands-on experience with AWS cloud services, including SageMaker, Lambda, Redshift, and infrastructure-as-code (Terraform).
Experience developing and maintaining MLOps pipelines and integrating ML models into production systems.
Proficiency in CI/CD pipelines with tools like Octopus Deploy, Git, and automated testing frameworks.
Proficiency in data extraction, transformation, and feature engineering from large, complex datasets.
Strong ability to prioritize, execute tasks efficiently, and solve complex technical challenges.
A proactive and curious mindset, with a willingness to explore innovative solutions.
Excellent communication skills and presentation skills, with the ability to collaborate across teams and mentor colleagues.
Ability to document processes, methodologies, and best practices for knowledge sharing.
Experience with vector databases (e.g., Pinecone, PostgreSQL) for AI applications.
Familiarity with Graph Neural Networks (GNNs) or knowledge representation techniques.
