Data Scientist - Logistics at The South African Breweries (SAB)

Job purpose:

The key purpose of this role is to identify opportunities, design and build analytics models that will bring efficiencies/optimize the logistics operation. This will involve gaining on site operational experience and understanding and then working with all logistics operations and tech teams to design and implement the analytics models into our existing application tech land scape.

Key roles and responsibilities

• Gain hands on in depth experience of the logistics operation on site.
• Delve for insights in data and processes, Identify opportunities and develop predictive and prescriptive models to enable better decision making and automation of business processes.
• Identify, understand and interpret data structures across various databases within the business to facilitate data analysis and continuous monitoring of activities..
• Participate and/or lead processes with business stakeholders to identify problems and opportunities that may be addressed with statistical modelling or machine learning.
• Identify and develop the hypothesis testing framework and modelling approach to address the business requirements.
• Make strategic recommendations on data collection and experimental design incorporating business requirements and knowledge of best practices.
• Prepare the data for analysis and modelling, which includes data cleaning, standardisation, transformation, dimension reduction and feature engineering.
• Identify and train suitable models/algorithms to discover patterns and make predictions.
• Extend existing code and develop custom code to implement statistical models, machine learning algorithms and data mining techniques for large datasets in a computationally efficient manner.
• Work with the tech teams to connect/implement predictive and prescriptive models into existing applications
• Compare model performance, select the best algorithm and be able to motivate this choice in a non-technical manner.
• Interpret results and translate findings into clear and actionable insights that can be easily validated with the project sponsor.
• Communicate findings to business with various skill levels and in various roles, presenting trends, correlations and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights.
• Assist business users in the use of the models and interpretation of model output.
• Deploy ML models to production on cloud platforms such as AWS, Google Cloud, or Azure or work with the tech teams to imbed in existing application Assist with monitoring and reporting on model accuracy after it has been embedded in operations.
• Develop and maintain productive and collaborative working relationships with peers and stakeholders.
• Positively influence and participate in change initiatives.Continuously develop ones’ own expertise in terms of professional, industry and legislation knowledge.
• Contribute to continuous innovation through the development, sharing and implementation of new ideas.

Profile

• Completed BSc degree or other related fields
• 2 years experience in data science
• Proficiency in programming languages such as SQL and Python
• In-depth knowledge of machine learning modelling libraries (e.g., scikit-learn, PyTorch, Tensorflow)
• Experience with deep learning and natural language processing will be advantageous
• 2-5 years’ data analysis experience
• Familiarity with visualisation tools (e.g. Tableau, PowerBI, Plotly)
• Experience in designing and building production systems in AWS, Google Cloud, or Azure
• Exposure to continuous integration/continuous deployment (CI/CD)
• Familiarity with version control systems (e.g., Git or AWS Commit)