Developing a Data Science Talent Pipeline Programme for Nigerian Technology Companies

The shortage of skilled data science professionals limits Nigerian technology companies' capacity to develop competitive analytics products, and a professionally designed talent pipeline programme can address this structural skills gap systematically. This study developed a data science talent pipeline programme framework for Nigerian technology companies in the Lagos-Abuja technology corridor. A professional programme design methodology was applied, incorporating a skills demand survey of 60 technology companies, structured interviews with 15 data science hiring managers and 8 university computer science department heads, and benchmarking against Google Career Certificates, IBM Data Science Professional Certification, and Andela's talent development model. The survey confirmed that SQL proficiency, Python for data manipulation, machine learning fundamentals, and communication of analytical results were the four most demanded but insufficiently supplied competencies in the talent market. The pipeline programme designed specifies a three-tier progression: bootcamp foundation (3 months), apprenticeship placement (6 months), and professional certification examination. University partnership provisions enable academic credit recognition. Programme governance, mentor network, and employer co-investment models are specified. Expert review by 12 data science education and human capital specialists confirmed the programme's design coherence. The study recommends launch through a consortium of five Lagos-based technology companies and two federal universities, with NITDA accreditation pursued within the first year of operation to legitimise the certification in public sector hiring decisions.

Keywords: data science talent, skills pipeline, Nigeria, technology workforce, professional training