Data Scientist III
Retail, Wholesale / FMCG
Minimum Requirements
- Master’s Degree in Data Science, Computer Science, Mathematics, Statistics, Information Technology, Information Systems, Engineering, or a related field – (essential).
- 8 years' experience in a Lead Data Scientist role, consistently leading and solving complex business and tech problems within a fast-paced environment – (essential)
- in coaching and mentoring others whilst taking ownership for specific project outcomes – (essential).
- delivering project outcomes using design thinking, lean and agile principles – (essential).
- in a retail, commercial or IT environment – (highly desired).
- Expertise in SQL, Python, Tableau, MatLab, and Large Datasets, Excel, R, Low Code skill, Generative AI, RAG, Standards & Best Practice Research Adoption – (essential).
- Strategic leadership in analytics, innovation
- Advanced statistical modeling, Decision-Making – (essential).
- The purpose of the Principal Data Scientist role is to oversee complex data solutions driving data as a commercial advantage for Shoprite and mentoring and coaching data scientists in the team to create a high-performing team. A conceptual and critical thinker, providing insights that enable innovation and best practices in a big data environment.
- Job Objectives
- Drive the development of Shoprite’s data strategy to deliver best-in-class analytics across the organisation.
- Lead engagements with business stakeholders to identify business requirements and model and frame business scenarios that are meaningful and which impact on critical business processes and/or decisions.
- Liaise with data and software teams to shape and enable deployment of fit-for-purpose, robust solutions that will scale across the company’s ecosystem.
- Define, develop and prioritise data projects and delegate assigned roles and responsibilities for execution, weighing business and technical trade-offs as required.
- Drive the development of analytics-focused products, using machine learning, natural language processing, and mathematical / statistical techniques to develop powerful sciences that delivers business value and impact.
- Manage the data scientist team to define models to be created and implemented together with the approach for implementing them and monitor for accuracy, integrity and robustness.
- Define data quality expectations and provide ongoing tracking and monitoring of performance of data systems and models.
- Develop sophisticated data preparation in order to reduce and shape data.
- Define comprehensive set of predictive and descriptive modelling techniques to the data appropriate to achieving the business objectives which includes decision trees and association rules.
- Identify and manage data development challenges, offer suggestions, and deploy appropriate solutions.
- Report on analytical findings and results to senior stakeholders, using data visualisation techniques to tell compelling stories, while tying progress to enterprise goals.
- Evaluate new and emerging technologies from which to develop prototypes and proof of concepts.
- Act as a domain expert, sharing best practices and knowledge with data scientists, analysts and cross functional partners.
- Act as a mentor and guide to data scientists on complex problems, integration of findings or presentation of results, requiring high-level expertise.
- Act in a technical leadership capacity, coaching and mentoring data scientists and new team members and supporting their growth and professional development.
- Research developments in Data Science and adjacent fields to ensure the latest technology, techniques and methods are always applied.
- Knowledge and Skills
Responsibilities
- Drive the development of Shoprite’s data strategy to deliver best-in-class analytics across the organisation.
- Lead engagements with business stakeholders to identify business requirements and model and frame business scenarios that are meaningful and which impact on critical business processes and/or decisions.
- Liaise with data and software teams to shape and enable deployment of fit-for-purpose, robust solutions that will scale across the company’s ecosystem.
- Define, develop and prioritise data projects and delegate assigned roles and responsibilities for execution, weighing business and technical trade-offs as required.
- Drive the development of analytics-focused products, using machine learning, natural language processing, and mathematical / statistical techniques to develop powerful sciences that delivers business value and impact.
- Manage the data scientist team to define models to be created and implemented together with the approach for implementing them and monitor for accuracy, integrity and robustness.
- Define data quality expectations and provide ongoing tracking and monitoring of performance of data systems and models.
- Develop sophisticated data preparation in order to reduce and shape data.
- Define comprehensive set of predictive and descriptive modelling techniques to the data appropriate to achieving the business objectives which includes decision trees and association rules.
- Identify and manage data development challenges, offer suggestions, and deploy appropriate solutions.
- Report on analytical findings and results to senior stakeholders, using data visualisation techniques to tell compelling stories, while tying progress to enterprise goals.
- Evaluate new and emerging technologies from which to develop prototypes and proof of concepts.
- Act as a domain expert, sharing best practices and knowledge with data scientists, analysts and cross functional partners.
- Act as a mentor and guide to data scientists on complex problems, integration of findings or presentation of results, requiring high-level expertise.
- Act in a technical leadership capacity, coaching and mentoring data scientists and new team members and supporting their growth and professional development.
- Research developments in Data Science and adjacent fields to ensure the latest technology, techniques and methods are always applied.
