Data Scientist

6 days ago

Sandton, Gauteng, South Africa Pepkor Lifestyle Full time R1 200 000 - R2 000 000 per year

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 optimize business outcomes.
  • Applying machine learning algorithms to solve business problems, including classification, regression, clustering, and recommendation systems.
  • Creating compelling visualizations 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 optimize business processes.
  • Staying updated with the latest advancements in data science and technology to bring innovative solutions to the team.

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