Data Scientist

Bidvest Facilities Management
Centurion
ZAR 300 000 - 400 000
Job description

Description
The Data Scientist will be responsible for designing and developing advanced data models and algorithms, leveraging machine learning, neural networks, and AI techniques to extract actionable insights from complex data sets. This role involves applying ML/NN/AI-driven solutions to optimize business processes and drive innovation. The Data Scientist must effectively communicate complex results to both technical and business stakeholders, ensuring alignment with organizational goals.


Tasks

  1. Collaborate with a diverse range of stakeholders to understand operational contexts and data requirements, ensuring that data initiatives align with business objectives.
  2. Stay abreast of the latest developments in machine learning algorithms and AI techniques, applying them to real-world business problems to drive innovation and efficiency.
  3. Design, implement, and validate models that address specific business cases, enhancing decision-making and operational efficiency.
  4. Continuously monitor and evaluate the performance of deployed models, identifying opportunities for improvement and optimization to maintain high accuracy and relevance.
  5. Proactively identify and improve processes and databases, ensuring data quality and accessibility to support advanced analytics.
  6. End-to-end analysis of data, encompassing gathering, processing, and analysis, culminating in the synthesis of innovative solutions and improvements to business problems.

Qualifications:

  1. Bachelor's degree or higher in Computer Science, Statistics, Mathematics, Engineering or related field.
  2. Matric/Grade 12.
  3. Valid SA driver’s license.

Experience:

  1. 5 years Data Scientist experience in Data Visualisation and Data Analysis. Have a solid understanding of business and financial process performance improvement.
  2. Experience in Facilities Management or Property Management industries will be advantageous.

Stack Tech:

  1. Proficiency in programming languages such as Python, R, and SQL.
  2. Data Science, Statistics, and Data Analytics skills.
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