Key skills
AI/GenAIMachine learningDeep learningAgentic AI systemsPythonRTensorFlowPyTorchscikit-learnHealthcare dataLife sciences dataEHR dataGenomic dataClinical trial dataBiomedical datasetsStatisticsData analysisExperimental designData preprocessingFeature engineeringModel validationAWSAzureGCPAI solution deploymentAIMachine LearningMLDeep LearningGenAIAgenticCommunicationCritical Thinking
About this role
IBM Consulting is dedicated to building long-term relationships and collaborating closely with clients globally. The role involves designing and developing AI models for healthcare applications, analyzing large datasets, and collaborating with cross-functional teams to integrate AI solutions into clinical workflows.
Responsibilities:
- Design and develop AI/GenAI models tailored for Healthcare and Life Sciences applications
- Analyze large datasets (structured and unstructured) to extract actionable insights
- Collaborate with cross-functional teams including clinicians, biostatisticians, and software engineers to integrate AI solutions into workflows
- Develop and validate predictive models for patient outcomes, treatment optimization, and clinical decision support
- Implement agentic AI systems that can autonomously perform tasks or provide recommendations in healthcare processes
- Conduct experiments and performance evaluations to ensure model accuracy, fairness, and reliability
- Stay up-to-date with AI/ML trends, particularly in GenAI and Healthcare applications, and propose innovative solutions
- Document methodologies, results, and AI model pipelines for reproducibility and regulatory compliance
- Support deployment and monitoring of AI solutions in production environments
Requirements:
- Proven experience in AI/GenAI and machine learning model development, including deep learning and agentic AI systems
- Strong programming skills in Python, R, or similar languages, and experience with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn)
- Experience with healthcare or life sciences data, including EHR, genomic, clinical trial, or other biomedical datasets
- Solid understanding of statistics, data analysis, and experimental design
- Experience in data preprocessing, feature engineering, and model validation
- Familiarity with cloud platforms (AWS, Azure, GCP) and deployment of AI solutions in production
- Ability to collaborate with multidisciplinary teams, including clinicians, software engineers, and product managers
- Strong problem-solving skills and critical thinking, with the ability to translate business or clinical needs into AI solutions
- Excellent communication skills to present findings, methodologies, and insights to both technical and non-technical stakeholders
- Master's Degree
- Experience with regulatory and compliance requirements in healthcare or life sciences is a plus