Role Overview
We are looking for a Data Scientist to design, develop, and deploy machine learning models that support advanced analytics and decision-making within healthcare and medical data environments.
In this role, you will work closely with product managers, software engineers, data engineers, and business stakeholders to build AI/ML solutions that integrate with enterprise platforms such as MSI and Medical Analytics systems.
This is an excellent opportunity for a hands-on Data Scientist who enjoys taking models from experimentation through to production deployment and ongoing monitoring.
Key Responsibilities
Machine Learning Model Development
- Design, develop, and train machine learning models for predictive analytics, classification, forecasting, and decision support.
- Perform exploratory data analysis, feature engineering, and model selection.
- Evaluate model performance using appropriate statistical and machine learning metrics.
- Fine-tune models to improve accuracy, robustness, and scalability.
AI Solution Deployment
- Deploy machine learning models into production environments
- Integrate models with MSI and Medical Analytics platforms
- Build inference pipelines and APIs to operationalise model predictions
- Collaborate with software engineers to productionise AI solutions
Model Monitoring & Validation
- Implement model monitoring to track performance, drift, and data quality
- Establish validation and retraining pipelines
- Document model assumptions, methodologies, and performance metrics
- Support responsible AI and governance requirements
Stakeholder Collaboration
- Work with stakeholders to understand business requirements and translate them into AI/ML solutions
- Present findings, insights, and recommendations to both technical and non-technical audiences
- Collaborate with data engineers to ensure reliable and high-quality data pipelines
Required Skills & Experience
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field
- 3+ years of hands-on experience building and deploying machine learning models
- Strong proficiency in Python
- Experience with machine learning libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch
- Experience with SQL and data analysis
- Familiarity with AWS SageMaker for model development and deployment
- Understanding of model monitoring, validation, and drift detection
- Strong analytical and problem-solving skills
- Excellent communication and stakeholder management skills
