Data Scientist - Machine Learning in R&D

About the Role

Our client is looking for a talented Data Scientist with a specialization in Machine Learning to join their innovative Research & Development department in Sunderland . In this critical role, you will harness the power of advanced machine learning techniques to solve complex scientific challenges, analyze large datasets, and drive product innovation. You will work within a highly collaborative team of scientists and engineers, translating complex data into actionable insights that shape the future of our client's offerings. This position is office-based, providing a dynamic environment for direct interaction and on-site collaboration.

Key Responsibilities

• Design, develop, and deploy machine learning models for prediction, classification, and anomaly detection using diverse scientific datasets.
• Clean, process, and analyze large, complex datasets to identify trends, patterns, and insights relevant to R&D objectives.
• Collaborate with subject matter experts to understand research questions and translate them into data science problems.
• Evaluate and benchmark different machine learning algorithms and approaches to ensure optimal performance and accuracy.
• Communicate complex findings and model results clearly to both technical and non-technical stakeholders.

Requirements

• Master's or PhD in Data Science, Computer Science, Statistics, Physics, or a related quantitative field.
• Proven experience (3+ years) in applying machine learning techniques to real-world problems.
• Strong programming skills in Python or R, with experience in libraries like TensorFlow, PyTorch, scikit-learn.
• Solid understanding of statistical modeling, data mining, and predictive analytics.
• Excellent problem-solving abilities and a keen eye for detail in data analysis.

Benefits

• Competitive annual salary and performance bonus.
• Comprehensive health, dental, and vision insurance plans.
• Opportunities for professional development and attending industry conferences.
• Access to cutting-edge computing resources and research facilities.
• A stimulating and collaborative team environment focused on scientific advancement.