Senior Data Scientist at Sasol

The Senior 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 & prescriptive intelligence for business applications.

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 Senior 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 also support the embedding of data capabilities and way of working within the business.

He/she will stay abreast of new/alternative techniques and/or tools for relevant application in the Sasol Energy business.

In addition, the senior data scientist will support and mentor junior data scientists in team.

Recruitment Description / Key Accountabilities

1. Lead and influence the design, engineering, development and modifications of Data Science products in accordance with sound analytical principles and data science standards to satisfy business requirements.
2. 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).
3. Define, apply and update Data Science best practices and standards.
4. Ensure that solutions are sustainable and adequately packaged for support handover.
5. Play Lead Data Scientist role on multiple projects that may apply Agile/Waterfall project execution.
6. Validate own and other's work to identify possible areas for improvement of efficiency, effectiveness to ensure and improve the quality and accuracy of the data science products.
7. Provide guidance to inexperienced team members as and when required.
8. Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
9. Actively seek customers where support could be offered and proactively identify real business needs.
10. Research trends in data science tools and techniques for continuous improvement.
11. Participate in and contribute to the Sasol Data Science CoP sessions and share own ideas / knowledge / experience within the Sasol Data Science community.

Formal Education

4-year Bachelor’s degree ideally in Statistics / Mathematics / Data Science / Operations Research / Engineering. Master’s degree in above will be advantageous.

Min Experience

1. At least 8 years of relevant business experience with excellent record of project delivery using more than one of the following data science modelling techniques (statistical, machine learning, simulation, optimisation).
2. Fluency in computer programming and data structures, with advanced capabilities in using data science toolkits such as R & Python. Excellence in R is ideal.
3. Demonstrated experience in implementing ML algorithms in the production instance together with the necessary end-to-end data pipelines to address specific business problems.
4. Experience in Agile project delivery is required
5. Experience as a data scientist with one of the big tier consulting firms.
6. Previous data science delivery in retail / go-to-market sector with focus in one or more areas of price & promotion optimisation / margin or cost optimisation / inventory optimisation /sales and operations planning will be preferred.
7. Experience in any of the following (Cloud (preferably Azure), Databricks, SQL, Docker, Spark, RShiny, PowerBI, Git)

Competencies

1. Analytics: The systematic computational analysis of data or statistics
2. Collaboration: The action of working with someone to produce something
3. Critical reasoning: The action of critically thinking about something in a logical, sensible way and taking all factors into consideration.
4. Data Management: Knowledgeable of the theory, purpose, architecture and design of the management, administration and relationships of the organization's data.
5. Execution capability: The underlying ability to execute a strategy/project or day to day work
6. 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.
7. Self-Mastery: Takes accountability for driving own growth through developing self-awareness, reflecting, seeking feedback and self-correcting
8. Tech Savvy: Knowledge of the Information Technology Industry including trends, emerging technology, best practices, competition, regulations, and legislation.