Data Scientist - Pepkor Lifestyle Corporate - IT - Sandton

JD Group; Johannesburg; On-site; ZAR 500,000 - 700,000; Full time

Job summary

A dynamic retail company is seeking a Data Scientist in Johannesburg to design and build advanced analytical models. The ideal candidate will possess a strong background in data science, outstanding programming skills in Python, and the ability to communicate complex data insights effectively. Responsibilities include model development, engaging in cross-functional collaboration, and continuous innovation within the analytics space. This role offers opportunities to influence business decisions through data-driven insights.

Qualifications

• An Honours degree in a quantitative field such as Data Science.
• High proficiency in Python and strong SQL skills.
• Deep understanding of statistical concepts and modelling techniques.

Responsibilities

• Design, build, and deploy machine learning models to predict outcomes.
• Analyze complex datasets to identify patterns and trends.
• Translate findings into narratives and visualizations for stakeholders.

Skills

Python programming

Statistical analysis

Machine learning

SQL

Data visualization

Communication

Critical thinking

Education

Honours degree in a quantitative field

Master’s degree or PhD in a quantitative field

Tools

Power BI

Tableau

SAS Visual Analytics

Apache Spark

AWS

Job description

Job title : Data Scientist - Pepkor Lifestyle Corporate - IT - Sandton

Job Location : Gauteng, Johannesburg Deadline : September 05, 2025 Quick Recommended Links

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Key Responsibilities

Model Development & Implementation : Design, build, and deploy robust statistical and machine learning models (e.g., for classification, regression, clustering) to predict outcomes and optimise key business metrics.

Advanced Analytics : Dive deep into large, complex datasets to identify meaningful patterns, trends, and causal relationships that answer critical business questions.

Data Storytelling & Visualisation : Translate complex analytical findings into clear, compelling narratives and visualisations for both technical and non-technical stakeholders using tools like Power BI, Tableau, or SAS Visual Analytics.

Data Preparation & Engineering : Take ownership of the data lifecycle, including cleaning, pre-processing, and transforming raw data into high-quality, analysis-ready datasets.

Experimental Design : Design and execute A / B tests and other experiments to validate hypotheses and measure the impact of new strategies.

Cross-Functional Collaboration : Partner closely with business analysts, data engineers, and product managers to define project requirements, develop solutions, and integrate them into our operational workflows.

Continuous Innovation : Stay current with the latest advancements in data science, machine learning, and AI, and champion the adoption of new technologies and methodologies within the team.

Skills & Qualifications

We believe the right candidate will have a blend of technical expertise, business acumen, and strong interpersonal skills.

Required :

Education : An Honours degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or Econometrics.

Core Programming : High proficiency in Python (including libraries like pandas, NumPy, scikit-learn) and / or SAS, paired with strong SQL skills for data extraction and manipulation.

Statistical Foundation : A deep understanding of statistical concepts, experimental design, and modelling techniques.

Machine Learning : Hands-on experience developing and deploying machine learning models using libraries such as scikit-learn, TensorFlow, or PyTorch.

Communication : Exceptional ability to articulate complex technical concepts and findings clearly and concisely to diverse audiences.

Problem-Solving : Strong critical-thinking and analytical skills with a proven ability to solve ambiguous problems with data.

Preferred :

Education : A Master’s degree or PhD in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or Econometrics.

Data Visualisation : Demonstrable experience creating insightful dashboards and reports in tools like Power BI, Tableau, or SAS Visual Analytics.

Big Data Technologies : Familiarity with distributed computing frameworks like Apache Spark or Hadoop.

Cloud Platforms : Experience working with data services on cloud platforms such as AWS, Azure, or GCP.

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