Principal Data Scientist at Sasol

Short Description / Purpose of Job

• The Principal Data Scientist is responsible for preparing and analysing large data sets in order to apply appropriate data science techniques (statistics / simulation / optimisation / machine learning, etc.) to drive predictive and prescriptive intelligence for business applications.
• The Principal Data Scientist will be responsible for the design, engineering, development, operationalisation and modification of complex and/or specialised data science products in accordance with sound analytical principles and standards to drive critical value-adding business decisions.
• The Principal Data Scientist will forge strong relationships and partnerships with key stakeholders to understand business needs; develop data science products in a way that maximises user buy-in while recognising and capitalising on new improvement opportunities to extract business value.
• He/she will lead research and development efforts in the advancement of new data science techniques and and/or tools for relevant application in the Sasol Energy business.
• In addition, the principal data scientist is a subject matter expert and will lead own projects as well as provide support to and mentor other data scientists in the team.

Recruitment Description/ Key Accountabilities

• Translate business questions and opportunities into specific quantitative questions that can be answered with available data using appropriate data science techniques (statistics/ simulation/ optimisation/ machine learning, etc).
• Define, apply and update Data Science best practices and standards.
• Ensure that solutions are sustainable and adequately packaged for support handover.
• Peer review other data scientists' work to identify possible areas for improvement of efficiency, effectiveness to ensure and improve the quality and accuracy of the data science products.
• Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
• Actively seek customers where support could be offered and proactively identify real business needs.
• Research trends in data science tools and techniques for continuous improvement and lead relevant piloting work to test and implement these tools/techniques.
• Contribute to the data science community as the subject matter lead on specific topics

Formal Education

• Master's degree ideally in Statistics / Mathematics / Data Science / Operations Research / Engineering. PhD in one of the above fields will be advantageous.

Min Experience

• At least 13 years of applied experience using advanced analytics, statistical methods and data science.
• Fluency in computer programming and data structures, with expert coding capability in R/Python and SQL.
• Applied data science delivery in any of the following areas: retail / customer loyalty, price & cost optimisation / inventory optimisation / sales and operations planning / digital twins will be preferred.
• Experience in Agile project delivery is required.
• Demonstrated thought leadership in the field of data science
• Applied experience in deep learning techniques (e.g. NLP, computer vision, etc.) is preferred, but not essential.
• Good presentation and communication skills with a knack for explaining complex analytical concepts to people from other fields
• At least 4 years experience in any of the following: distributed computing, Databricks, Spark, containers, Git, and building effective CI/CD pipelines, PowerBI, web frameworks
• Azure certifications are preferred.

Competencies

• Analytics: The systematic computational analysis of data or statistics
• Collaboration: The action of working with someone to produce something
• Critical reasoning: The action of critically thinking about something in a logical, sensible way and taking all factors into consideration.
• Data Management: Knowledgeable of the theory, purpose, architecture and design of the management, administration and relationships of the organization's data.
• Execution capability: The underlying ability to execute a strategy/project or day to day work Problem Solving: Is a step-by-step process of defining a problem, searching for information, and testing a series of solutions until the problem is solved. In involves critical thinking, analysis and persistence.
• Self-Mastery: Takes accountability for driving own growth through developing self-awareness, reflecting, seeking feedback and self-correcting
• Tech Savvy: Knowledge of the Information Technology Industry including trends, emerging technology, best practices, competition, regulations, and legislation.