IMO Health is a clinical data intelligence company, improving how data is used across the healthcare landscape
The Role
The Staff Data Scientist will design and optimize AI-driven machine learning models for healthcare applications, ensuring data privacy and collaboration with experts.
Summary Generated by Built In
At IMO Health, a core team of software developers, data scientists, and domain experts combine computer science, healthcare, and life sciences expertise to help professionals access high-quality health information quickly and easily. We need a Staff Data Scientist, Life Sciences AI with a strong background in building and maintaining AI-driven solutions to join this team!
In this role, you will design, develop, and optimize machine learning models for real-world life sciences and 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 Staff Data Scientist, Life Sciences AI to drive AI-powered innovation that advances biomedical research, clinical development, and real-world evidence.
WHAT YOU'LL DO:
- Leverage machine learning, deep learning, prompt engineering, and data mining technologies to develop AI-driven solutions for life sciences and healthcare use cases.
- Collaborate with domain experts to ensure the relevance and accuracy of data-driven insights.
- Ensure data privacy and security compliance in all data handling and processing activities.
- Evaluate and implement feedback mechanisms to improve AI solutions.
- Develop knowledge graphs and structured data representations to enhance AI-powered insights.
- Develop and maintain data 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.
- Follow software engineering best practices to write clean, reliable, and testable code, supporting rapid delivery via CI/CD and automated deployments.
- Explore new technologies, proof-of-concepts (PoCs), and technical roadmaps.
- Work closely with 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.
- Mentor team members, fostering technical growth and skill development in machine learning, NLP, and AI research.
- Foster a culture of continuous learning, staying up to date on AI technologies, analytics tools, and industry best practices.
WHAT YOU'LL NEED:
- Master’s degree in Statistics, Data Science, Computer Science, or a related field; PhD preferred.
- Master’s degree with a minimum of 5 years of relevant work experience; or PhD with no work experience required.
- 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, Agentic AI (such as Langchain, MCP, Langraph), 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.
- Demonstrated ability to contribute to scientific publications in the life sciences or healthcare domain.
Top Skills
AWS
Git
Lambda
Octopus Deploy
Python
PyTorch
Redshift
Sagemaker
TensorFlow
Terraform
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The Company
What We Do
We are a team of dedicated clinical terminologists, data scientists, industry subject matter experts, and informaticists who helped facilitate the evolution from analogue to digital capture of clinical events, the precise code-mapping that simplifies complex workflows, and the translation of unstructured into structured data. We “wrote the digital dictionary” used in every major EHR, and we are leveraging clinical AI to generate insights that expand and deepen our impact across the healthcare ecosystem.
At the end of the day, we don’t make decisions for our clients. We provide them with the digital tools to enable sound decision-making.
Why Work With Us
We are building a clinical intelligence stack—medical ontology, human expertise, and AI—that makes data more useful and more powerful. By enhancing data’s structure, richness, and precision, we reduce noise and error, streamline complexity, and create clarity across the clinical information chain.
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