Lead Data Scientist - Machine Learning

About the Role

Our client is seeking an experienced and innovative Lead Data Scientist specializing in Machine Learning to spearhead their data-driven initiatives in Newcastle upon Tyne . This role involves leading a team of data scientists to develop and deploy advanced predictive models and algorithms that provide actionable insights and drive strategic business decisions. You will work closely with product managers, engineers, and stakeholders to identify opportunities for ML applications and translate complex data into tangible business value. This position offers a unique opportunity to shape the future of data science within the company, fostering a collaborative environment where cutting-edge research meets real-world application, with the flexibility of a hybrid working model.

Key Responsibilities

• Lead the design, development, and implementation of complex machine learning models and algorithms.
• Mentor and guide a team of data scientists, fostering their professional growth and ensuring project success.
• Collaborate with stakeholders to identify business challenges and translate them into data science problems.
• Oversee the end-to-end data science workflow, from data extraction and cleaning to model deployment and monitoring.
• Stay abreast of the latest advancements in AI, ML, and data science, and evaluate their potential application.
• Communicate complex findings and insights clearly to both technical and non-technical audiences.

Requirements

• Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 7+ years of experience in data science , with at least 2 years in a leadership role.
• Proven track record of developing and deploying successful machine learning solutions in production.
• Expertise in statistical modeling, data mining, and predictive analytics.
• Proficiency in programming languages such as Python or R and associated libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong experience with SQL and big data technologies (e.g., Spark, Hadoop).

Benefits

• Competitive salary package with performance-based incentives.
• Hybrid working model offering flexibility between office and remote work.
• Comprehensive private healthcare coverage.
• Generous pension scheme.
• Opportunities for continuous learning and professional development, including conference attendance.