Human Resources Officer @ Pepkor Lifestyle Job Purpose As a Data Scientist at Pepkor Lifestyle, you will play a crucial role in analysing and interpreting complex data sets to inform business decisions and strategies. The ideal candidate has excellent analytical abilities, a deep understanding of statistical modelling, and the ability to communicate insights effectively to non-technical stakeholders. Minimum qualification and Experience Master's or Ph.D. in Data Science, Statistics, Computer Science, Mathematics or a related field. Proven experience as a Data Scientist with a strong portfolio of projects. Proficiency in programming languages such as Python or SAS. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of statistical concepts and methodologies. Excellent data visualization skills using tools like Tableau, Power BI, or Matplotlib. Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus. Excellent communication skills with the ability to convey complex findings to both technical and non-technical stakeholders. Strong problem-solving and critical‑thinking skills. Experience with SQL and relational databases. Position outputs/competencies Utilizing advanced analytics techniques to analyse large, complex datasets and extract meaningful patterns and trends. Developing and implementing statistical models to predict and optimise business outcomes. Applying machine learning algorithms to solve business problems, including classification, regression, clustering, and recommendation systems. Creating compelling visualisations to communicate insights and findings to both technical and non-technical audiences. Working closely with cross‑functional teams, including business analysts, data engineers, and software developers, to understand business requirements and objectives. Cleaning, pre‑process, and wrangle raw data into a usable format for analysis. Designing and analysing experiments to test hypotheses and optimise business processes. Staying updated with the latest advancements in data science and technology to bring innovative solutions to the team. Seniority level Mid‑Senior level Employment type Full‑time Job function Information Technology Industries Retail #J-18808-Ljbffr