Environment jobs in South Africa

Are you an experienced and inquisitive individual with a passion for data? Join our team as a Data Scientist and be a key player in shaping our data-driven future.

Duties and Responsibilities:

• Data Integrity: Leverage your expertise to process, cleanse, and ensure the integrity of data used for analysis.
• Algorithm Development: Develop algorithms and create predictive models to enhance our product offerings.
• Machine Learning Techniques: Utilise machine learning techniques to improve data quality and generate reports with actionable insights.
• Collaboration: Collaborate with the team to present findings and recommendations effectively.

Requirements:

• Experience: 4+ years of working experience in Data Science.
• Education: Degree in quantitative fields like Mathematics, Statistics, Operational Research, Economics, or equivalent industry training and experience.
• Strategy Development: Experience in strategy development and implementation using advanced data analytics.
• Outsourced Environment: Experience working in an outsourced environment and effectively implementing solutions using both internal and external resources.
• Analytical Experience: least 4 years of analytical experience on a consumer portfolio dataset (retail, banking, telecoms, etc.).
• Team Collaboration: Worked with diverse teams to ensure effective implementation of projects.
• Programming Skills: Proficiency (intermediate or advanced level) in Python or equivalent analytical & statistical programming languages.
• Statistical Concepts: Understanding of key statistical concepts used in model development, evaluation, and hypothesis testing.
• Data Processing Tools: Exposure to data processing tools like Spark or Hadoop for working with large-scale datasets (Exposure to cloud platforms like AWS advantageous).
• Microsoft Office: Proficiency in Microsoft Office (Excel, Word, PowerPoint, etc.), ideally using macros.
• Machine Learning Knowledge: Outstanding knowledge of machine learning techniques and algorithms, including clustering methods, neural networks, and boosting algorithms.