Senior R&D Engineer - Data Science

Smith & Nephew•Pittsburgh, PA

1d•Hybrid

About The Position

Life Unlimited. At Smith+Nephew we design and manufacture technology that takes the limits off living. Join our AI Center of Excellence and help shape the future of healthcare innovation. As a Senior R&D Engineer, Data Science based in Pittsburgh, PA, you will develop advanced AI and machine learning solutions that support products across orthopedics, wound care, and sports medicine. This is an exciting opportunity to work on complex real-world challenges, transform research into practical solutions, and collaborate with multidisciplinary teams that are advancing medical technology. This position does not offer visa sponsorship now or in the future.

Requirements

Bachelor's degree in Data Science, Mathematics, Artificial Intelligence, Computer Science, Computer Engineering, or a related discipline.
3 to 6 years of experience applying machine learning tools in research, academic, or industrial environments.
Strong Python programming skills and hands on experience with data science and machine learning libraries including NumPy, Pandas, Scikit learn, TensorFlow, PyTorch, and Keras.
Experience building end to end machine learning workflows from data preparation through model evaluation and prototyping.
Strong understanding of statistical modeling, data analytics, and experimental design, with the ability to communicate complex technical findings to diverse audiences.
Ability to work independently on complex technical challenges in a fast paced, collaborative environment.
Ability to travel up to 5% as required.

Nice To Haves

A Master's or Doctoral degree is preferred.

Responsibilities

Develop, implement, and validate advanced AI and machine learning solutions for healthcare and medical device applications.
Design, train, tune, and evaluate machine learning and deep learning models using industry leading frameworks and tools.
Research emerging AI and machine learning techniques and assessing their application to real world healthcare challenges.
Build and maintain data pipelines, prototype systems, scripts, and internal tools that support experimentation and model development.
Prepare, clean, and curate structured and unstructured datasets while developing effective feature engineering strategies.
Run experiments, analyze results, and validate model performance using appropriate statistical and evaluation methods.
Partners with AI researchers, R&D engineers, and product teams to integrate AI capabilities into broader solutions and workflows.
Document technical approaches, findings, and model behavior to support product development and decision making.
Contribute to a collaborative environment while mentoring less experienced engineers and supporting team success.