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Click-on Kaduna Data Science Fellowship Programme 2023

 

PIONEERING DATA SCIENCE EDUCATION: APPLY NOW FOR THE CLICK-ON KADUNA DATA SCIENCE FELLOWSHIP PROGRAMME 2023.

  • Applications are open for the Click-on Kaduna Data Science Fellowship Programme 2023, aiming to improve public policy and decision-making in Kaduna State through data-driven solutions. The 6-month program includes training and paid internship, offering a chance to work with the Kaduna State Bureau of Statistics and other agencies. Apply by July 21, 2023.

Click-on Kaduna Data Science Fellowship Programme

The Kaduna State’s Data Revolution Plan, designed to bolster data collection and its utilisation for evidence-based decision-making, proudly introduces the 2023 Data Science Fellowship Programme. Applications for this prestigious fellowship, powered by the Click-on Kaduna initiative, are now open, welcoming budding data management professionals to enrich their knowledge and expertise.

About The Programme: Promoting Data-Driven Innovation

The Click-On Kaduna Data Science Fellowship Programme is an advanced Digital Skills and Development Programme initiated by the Kaduna Bureau of Statistics. It aims to train 100 young individuals in Data Science, employing modern tools to enhance public policy and decision making in Kaduna State. This programme, part of the wider Kaduna State Data Lab Project, is a joint endeavour by the Kaduna State Government, Bill and Melinda Gates Foundation, and the Natview Foundation for Technology Innovation.

Spanning a total of six months, the programme combines a rigorous three-month training schedule followed by a three-month paid internship. The practical experience enables participants to work in close collaboration with the Amina J. Mohammed SDGs Data Lab under the Kaduna State Bureau of Statistics. Additionally, fellows may have opportunities to assist other State Ministries and Agencies, including the Ministry of Health, in data coordination efforts that bear a significant societal impact.

A World of Benefits

The fellowship promises numerous advantages:

  • It provides an opportunity to hone your skills and establish a career in a sought-after global industry.
  • It offers hands-on experience working with public sectors across Health, Education, Agriculture, and Infrastructure, making a tangible difference through the use of data.
  • It invites participation in development planning and public policy formation, promoting the use of data for evidence-based decision-making in the Health Sector.
  • It guarantees a six-month paid internship with industry leaders and stakeholders within the health sector.
  • It encourages modelling data using Artificial Intelligence and Machine Learning tools within the Amina J. Mohammed SDGs Data Lab.
  • It fosters networking within the Data Science Ecosystem.

Eligibility Criteria

Applicants must meet the following requirements:

  • Be aged between 18 and 35 years, with some exceptional cases considered.
  • Be a resident of Kaduna.
  • Have graduated from a tertiary institution, studying a STEM course, particularly Statistics, Mathematics, Computer Science, Engineering, Economics, Physical Sciences, or any other health-related discipline. STEM undergraduates undertaking a six-month to one-year internship are also encouraged to apply.
  • Possess skills in basic computer knowledge, basic data handling, understanding Microsoft Excel, problem-solving, and communication (both written and verbal English).
  • Please note, a 50% gender balance will be considered during the selection process.

How to Apply

Application involves a series of steps, beginning with the completion of an application form and culminating in the fellowship programme itself. The entire process is outlined in detail on the application webpage.

For further information, visit the Click-on Kaduna Data Science Fellowship page. The application deadline is 21st July 2023.

Seize this opportunity to transform your career and make an impact on society. Apply today and pave the way for a brighter, data-driven future.

 

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