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Head of Research

Job Description

To conduct fundamental and technical analysis of various asset classes and investment products using various available tools. Additionally, to conduct primary macro-economic research especially as it relates to these asset classes. To make recommendations to retail and institutional investors and support the investment decision making process.

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Financial 55%

  1. Undertake fundamental analysis on listed companies.
  2. Initiate and maintain macroeconomic and fixed income analysis.
  3. Build and maintain valuation models for listed and unlisted entities.
  4. Maintain a corporate action diary of quoted and unquoted companies.
  5. Ensure quality and product acceptability is maintained
  6. Maintain ongoing engagement with Senior management of listed entities to ensure reports are insightful and current
  7. Analyse financial information to produce forecasts of economic and industry conditions for use in making investment decisions.
  8. Identifying investment opportunities within the local and regional equity and fixed income markets via a variety of means, including quantitative analysis as well as building and leveraging off third party research networks.
  9. Conduct retail and institutional investor conference calls to discuss/market reports, as a result generate revenue.

Internal business processes 20%

  1. Ensure that all research carried out complies with all the relevant internal and external rules, regulations, policies and procedures
  2. Communicate all relevant and critical information to management in a timely and effective manner and in compliance with the company, NSE & CMA procedures

Customer 15%

  1. Ensure that Customer Service Standards are complied with and met at all times.
  2. Ensure turnaround times for research reports are met.
  3. Ensure customer complaints are dealt with expeditiously and conclusively in the first instance.
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Learning and growth 10%

  1. Takes responsibility for own training both formal and on the job
  2. Ensures compliance with the ICIFA annual training requirements
  3. Achieves at least 40 hours of training annually

Data Scientist

The Data Scientist is responsible for advising the business on the potential of data, to provide new insights into the business’s mission, and through the use of advanced statistical

analysis, data mining, and data visualization techniques, to create solutions that enable enhanced business performance.


  1. Bachelor’s degree in Statistics, Mathematics, Computer Science, Machine
  2. Learning, Economics, or any other related quantitative field. Working experience of the equivalent is also acceptable for this position.


Big Data or Data Science certification from recognized institutions

Desired work experience:

  • At least 3 years of working experience working with business analysis/informatics and business outcomes research within a fast-paced and complex business setting, preferably working as support data scientist junior support personnel
  • Experience working in probability and statistics, time-series analysis, or econometrics as well as experience in the use of machine learning methods, for example, linear regression, decision tress, and so forth.
  • Experience as well as in depth knowledge of the Python programming language, SAS Enterprise Miner and substantial knowledge of big data platforms such as Aster and Hadoop.


The Data Scientist also plays a leading role in the management of:

  • Build econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling and simulations
  •  Build the foundation of state-of-the-art scientific and technical capabilities within the Data Science department in order to support several planned and ongoing data analytics projects.
  •  Provide forward-thinking recommendations to the business by building in-depth understanding of the problem domain and available business data assets, especially those pertaining to strategic initiatives and value-based programs
  •  Execute ad-hoc data mining and exploratory statistics tasks on large data-sets related to the business ‘strategies.
  •  Generate actionable insights applying advanced statistical techniques, for example, predictive statistical models, segmentation analysis, customer profiling, analysis, survey design, and datamining
  •  Collaborate with senior data scientists to communicate obstacles and findings to relevant stakeholders in an effort to improve decision-making and drive business performance.


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