The Data Scientist department is constantly looking for the adoption of technology and currently has vast data that needs to be modeled, analyzed, interpreted with meaningful predictive outcomes. In this regard, the DS department is looking to add a Data Scientist to the team. The data scientist is expected to work with the stakeholders within and outside the organization in providing them with the data and it’s interpretation and solution


  • The individual should have a desire for data mining, scripting, problem-solving and statistical analysis.
  • The individual will be responsible for scripting data models, automating data feeds using BI tools to help visualize data and various ad hoc projects.
  • The individual will also need to drive statistical analysis projects from beginning to end and comes with (not required) working experience with regression, factor analysis, building models and predictive analytics.
  • Strong communication skills to obtain stakeholder buy-in and convince the audience on the quality of the delivered models are critical to this position.
  • To work collaboratively with data scientists and analysts.
  • Drive improvement in methodologies, systems, and processes.
  • Have a deep understanding of large data, our data structures, and how to manipulate our data in an efficient manner.
  • Have working experience with statistical tools such as SPSS and SAS, have the ability to create statistical models, analyze factors significant to driving user engagement and build predictive models based on historical data.


  • At least 1-3 years’ experience in Data Science
  • Expert in devising statistical algorithms
  • Equipped with Python knowledge, SQL, NoSQL, Excel, VBA, macros, queries, etc.
  • Great data visualization skills using Power BI, Tableau or any other sophisticated tools
  • Excellent communication skills and good attitude

Skills Profile

  • Strong analytical skills and facility with Excel (pivot tables, lookups, formulas, formatting)
  • Data, statistics, or other quantitative methods.
  • Programming, computer science, or engineering.
  • Domain under investigation.
  • Strong Business Understanding, Data Understanding, Data Prep and Modelling