Overview In this role, you advance AI and ML research within Smith+Nephew's AI Center of Excellence to tackle real-world healthcare challenges. You will prepare and structure large data sets, design meaningful feature representations, and train models that inform product development in orthopedics, wound care, and sports medicine. You work in a fast-paced, collaborative R&D environment to deliver accessible AI tools and insights for cross-functional teams. This position offers the chance to impact patient outcomes while growing your career in a leading medical technology company.
Compensation / Benefits- 401k Matching Program
- 401k Plus Program
- Discounted Stock Options
- Tuition Reimbursement
- Medical, Dental, Vision
- Health Savings Account (Employer Contribution)
Responsibilities- Research and evaluate state-of-the-art AI/ML models for potential product applications
- Prepare, clean, and structure large datasets for model development and training
- Design feature encodings to extract insights from complex data
- Develop, code, and train ML models using modern data science tools
- Validate and analyze model performance with statistical techniques
- Create intuitive interfaces/tools enabling teams to explore and use AI models
- Collaborate within a multidisciplinary, fast-paced R&D environment
Key requirements- Bachelor's degree in Data Science, AI, Computer Science, Mathematics, Computer Engineering or related field
- 1-3 years of experience applying machine learning in academic or professional settings
- Strong programming skills in Python, R, MATLAB or similar
- Experience with ML/data science libraries such as Scikit-Learn, TensorFlow, PyTorch, NumPy, Pandas, or Keras
- Solid understanding of data analytics and statistical methods
- Strong communication skills to clearly explain technical findings
- This position does not offer visa sponsorship now or in the future
- strong communication skills
- ability to explain technical findings clearly
- collaboration within multidisciplinary teams
- Python
- R
- MATLAB