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Job title: Data Scientist
Employment type: Full Time
Experience: 5 to 6 years
Salary: Negotiable
Job published: 10 December 2021
Job reference no: 2806687996

Job Description

Strategic Accountability:

Support the organisation by producing business insights through analysing organisational data.

Ensure data integrity and structures are optimise to enhance the organisational performance through better decision making.

Building the big data and AI foundational structures of the organisation

Work with business to optimise intelligence outcomes of business processes

Functional Accountability and Competencies Required:

  • Analytics
  • Collaboration
  • Business Understanding
  • Strategy / Design


Essential Work Experience:

3 – 5 years of experience manipulating data sets and building statistical models with hands-on experience in the below:

  • Is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
  • Minimum 3 + Years in SQL , Data Mining and R Programming
  • using statistical computer languages to manipulate data and draw insights from large data sets.
  • They must have a proven ability to drive business results with their data-based insights.
  • working with and creating data architectures.
  • advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
  • analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.


  • Qualification in Statistics, Mathematics, Computer Science or another quantitative field

Computer Skills:

Technical skills Requirement


  • For data manipulation, reading, aggregation, and visualization using tools such as Python programming and the use of Panda (data analysis library), C#, C++, Java, JavaScript, etc.

R programming:

To implement machine learning algorithms quickly and simply and provides a variety of statistical and graphical techniques, such as linear and non-linear modelling, classical statistical tests, time-series analysis, classification, and clustering.

Hadoop platform:

  • to process large datasets across clusters of computers using simple programming models.

SQL databases:

  • for managing and querying data held in a relational database management system

Machine learning and AI:

  • to analyze large chunks of data using algorithms and data-driven models and to automate significant parts of a data scientist’s job using tools such as regression, simulation, scenario analysis, modelling, clustering, decision trees, neural networks, etc.

Data visualization:

  • Data visualization is the graphical representation of data using visual elements such as charts, graphics, maps, infographics, and more using tools such Power BI, Periscope, Business Objects, D3, ggplot

Business strategy:

  • The ability to understand business problems and conduct analyses from the standpoint of a strong problem statement

Interpersonal Skills Requirement:

  • Communication
  • Storytelling
  • Collaboration
  • Learning