Lead Data Scientist

About the Role Our client is seeking a highly skilled and innovative Lead Data Scientist to guide their data analytics initiatives in Nelspruit . This leadership role involves developing and implementing advanced machine learning models, driving data-driven decision-making, and mentoring a team of data scientists. You will work on challenging projects involving large datasets, focusing on extracting actionable insights to improve business performance, customer experience, and operational efficiency.

This position offers a fantastic opportunity to influence the data strategy of a forward-thinking organization and foster a culture of data excellence.

• Lead the design, development, and deployment of machine learning models and data-driven solutions.
• Analyze complex datasets to identify patterns, trends, and opportunities for business growth.
• Mentor and guide junior data scientists, fostering their technical and analytical development.
• Collaborate with business stakeholders to understand their needs and translate them into data science projects.
• Develop and implement strategies for data collection, cleaning, and feature engineering.
• Communicate complex findings and recommendations clearly to both technical and non-technical audiences.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 7 years of experience in data science, with a proven track record of leading projects.
• Expertise in machine learning algorithms, statistical modeling, and data mining techniques.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, Tensor Flow, PyTorch).
• Strong experience with SQL and big data technologies (e.g., Spark, Hadoop).
• Excellent leadership, communication, and problem-solving skills.

• Highly competitive salary and performance-based bonuses.
• Opportunity to lead and shape the data science function within a growing company.
• Hybrid work model providing flexibility and balance.
• Comprehensive health and retirement benefits.
• Access to advanced tools and technologies for data analysis and model development.