Lead Data Scientist - R&D Analytics

Our client is looking for an experienced and innovative Lead Data Scientist to direct their R&D Analytics initiatives in Pretoria .

• Develop and deploy advanced machine learning models and algorithms to predict research outcomes, optimize experimental designs, and identify novel scientific trends.
• Lead the design and implementation of data infrastructure and pipelines for research data collection, processing, and analysis.
• Mentor and manage a team of data scientists, providing technical guidance and fostering a culture of innovation and collaboration.
• Collaborate with research scientists and engineers to understand their analytical needs and translate them into data science solutions.
• Communicate complex findings and recommendations clearly and effectively to both technical and non-technical stakeholders, including senior leadership in Pretoria .
• Ensure the quality, integrity, and reproducibility of all data science analyses and models.

• Master's or Ph.D. in Data Science , Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of professional experience in data science or advanced analytics, with demonstrated experience leading projects and teams.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, Tensor Flow, PyTorch).
• Strong understanding of statistical modeling, machine learning techniques, and experimental design.
• Experience working with large, complex datasets, including structured and unstructured data.
• Excellent communication, problem-solving, and leadership skills, with a passion for applying data science to scientific challenges in Pretoria .

• A highly competitive salary and a comprehensive benefits package, including health, retirement, and performance bonuses.
• Significant opportunities for professional development, training, and conference attendance.
• A dynamic and collaborative work environment with a focus on innovation and scientific advancement.
• Access to powerful computing resources and cutting-edge data analytics tools.
• Flexible work arrangements to support work-life balance.
• The chance to make a significant impact on R&D strategy and outcomes.