Data Scientist

5 months ago

Stellenbosch, South Africa Plus1X Solutions (Pty) Ltd Full time

Data Scientist - Contract (Hybrid - Stellenbosch)

 

Purpose Statement

To drive the AI strategy, ensuring the organization remains competitive in a dynamic landscape where data science is a key strategic differentiator. To design and implement predictive models and intelligent algorithms that enhance business performance and support improved decision-making.

Education

Minimum:

  • Honours Degree in Data Science

Preferred:

  • Masters Degree in Data Science

Knowledge and Experience

Minimum Requirements:

  • Master’s degree or equivalent in a quantitative discipline or STEM field (e.g., Mathematics, Statistics, Engineering, Computer Science) with a focus on Machine Learning, plus 6 years of relevant experience.
    Or
  • Honours Degree or equivalent with relevant technical qualifications, plus 8 years of relevant experience.
  • Experience in data science, machine learning, and deploying developed solutions.
  • Proficiency in business analysis and requirements gathering.
  • Experience in reproducible coding, working with relational and non-relational databases, and at least one machine learning language.
  • Experience working in cloud environments.

Ideal Requirements:

  • Experience collaborating with multiple teams to deliver predictive models into a production environment.
  • Proven ability in stakeholder management at Executive and senior management levels.

Knowledge

Minimum:

  • Deep understanding of state-of-the-art and emerging principles and techniques in at least one discipline of data science (e.g., NLP, Deep Learning) and the ability to teach these to a wide technical audience.
  • Strong grasp of the theory and application of machine learning models, with the ability to educate others.
  • Familiarity with modern deep learning frameworks (Tensorflow, PyTorch, MXNet, etc).
  • Best practices for data science.
  • Ethical AI design principles.

Ideal:

  • Understanding of the Data Science lifecycle and Data Product Life Cycle within an organization.

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