Africa is poised to become a leading source of innovation in a variety of sectors with an expected growth rate of 7% annually over the next 20 years. IBM recognizes the potential impact of research and smarter systems in helping to build Africa’s future, hence the African research lab creates technology applications in a range of industries at the core of Africa’s growth: financial services, education, healthcare, mobility, public safety and utilities. IBM believes that increasing access to financial services is a critical component. Our goal is to develop original and novel solutions to propagate access to financial services by employing data driven approaches on non-traditional data sources. We are focused on innovations that help the unbanked and under-banked gain access to formal financial services such as payments, savings, credit, insurance, and investments. IBM Research scientists are evaluated on three broad metrics: impact, engagement, and eminence. These metrics, in the context of a commercial research lab in an emerging market, create a unique combination of roles and responsibilities for a Financial Inclusion research scientist. Impact: - Develop technologies, analytics and algorithms in financial inclusion and financial services projects. - Identify data-driven methods when more traditional approaches are infeasible.- Transform research insights into real-world systems for use across the continent. Engagement: - Collaborate with local and international organizations to understand and solve the unique financial problems that arise in Sub-Saharan Africa. - Work closely with domain and technology experts at the Africa Lab as well as researchers from IBM’s Global Research organization spanning six continents.- Build research capacity by advising graduate students from top universities across the continent and throughout the world. Eminence:- Build a reputation in the academic community by publishing in high impact journals and outlets.- Establish thought leadership in the local financial community.- Develop a strong profile within the company with original contributions that drive impact for IBM.
Education and Experience:
M.S./M.Sc. in Computer Science, Statistics, Mathematics, Engineering or related field.
3 to 5 years of experience depending on education level. Recent graduates will be considered.
Knowledgeable of the many tools in machine learning, artificial intelligence, and data mining.
Exposure to a variety of programming languages such as C, Java, R or Python.