Senior Data Scientist

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! 

• 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.  

• 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.