Senior Data Scientist - R&D Analytics

Our client is seeking an experienced Senior Data Scientist to join their innovative Research & Development analytics team in Vereeniging . This role is central to extracting actionable insights from complex datasets generated during research processes, enabling data-driven decision-making. You will develop advanced analytical models, design experiments, and communicate findings to both technical and non-technical stakeholders. This is an exciting opportunity to leverage your expertise in data science to drive innovation and strategic direction within a leading research organization.

• Design and implement advanced statistical models and machine learning algorithms for R&D data analysis.
• Extract, clean, and transform large, complex datasets from various research sources.
• Develop predictive models and analytical solutions to identify trends, opportunities, and risks in research projects.
• Collaborate with researchers and engineers to define key performance indicators and analytical requirements.
• Create compelling data visualizations and dashboards to communicate complex findings effectively.
• Stay current with the latest advancements in data science, machine learning, and relevant research domains.

• Master's or Ph.D. in Data Science, Statistics, Computer Science, or a related quantitative field.
• Minimum of 5 years of professional experience as a Data Scientist , with a focus on R&D or scientific applications.
• Proficiency in programming languages such as Python or R, and experience with data manipulation libraries.
• Strong knowledge of machine learning techniques, statistical modeling, and experimental design.
• Experience with SQL and big data technologies.
• Excellent communication and presentation skills, with the ability to explain technical concepts to diverse audiences.

• Competitive salary and performance-based incentives.
• Comprehensive health, disability, and life insurance coverage.
• Opportunities for continuous learning and professional development in data science.
• Flexible work arrangements, including a hybrid model, supporting work-life balance in Vereeniging .
• A collaborative and innovative work environment focused on advancing scientific research through data.