Data Scientist - AI Specialization

About the Role

Our client is seeking a highly analytical and motivated Data Scientist with a specialization in AI to join their dynamic team in Sunderland, Tyne and Wear . In this role, you will leverage advanced statistical techniques and machine learning algorithms to extract valuable insights from complex datasets, driving data-informed decision-making across the organization. You will work on diverse projects, from building predictive models to developing novel AI applications, collaborating closely with business units to solve critical challenges. This is an exciting opportunity to contribute to impactful projects in a growing tech-focused environment.

Key Responsibilities

• Develop and implement statistical models and machine learning algorithms to analyze large, complex datasets.
• Identify trends, patterns, and insights that can inform business strategy and product development.
• Build predictive models for forecasting, classification, and anomaly detection.
• Design and conduct experiments to test hypotheses and validate findings.
• Communicate complex findings and recommendations clearly to both technical and non-technical stakeholders.
• Contribute to the development and deployment of AI-powered solutions.

Requirements

• Master's degree or PhD in Data Science, Statistics, Computer Science, or a related quantitative field.
• Proven experience as a Data Scientist, with a strong focus on AI and machine learning.
• Proficiency in programming languages such as Python or R, and relevant libraries (e.g., Pandas, NumPy, Scikit-learn).
• Solid understanding of statistical concepts, data mining techniques, and ML algorithms.
• Experience with data visualization tools and techniques.
• Excellent analytical, problem-solving, and communication skills.

Benefits

• Competitive salary with performance-based incentives.
• Extensive health, dental, and vision insurance coverage.
• Generous allowance for professional development and training.
• Flexible working hours and a strong emphasis on work-life balance.
• Access to advanced data analytics tools and a collaborative research environment.