What are the responsibilities and job description for the Senior Data Scientist position at IMO Health?
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!
\n- 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.
Salary : $131,000 - $178,000
