Data Scientist

About the job The Role Kofa is building a portable battery network to provide reliable energy access for our customers. The initial use case for these batteries is to power electric motorcycles, and ultimately, any relevant use case. To achieve this, we are building a network of charging stations where customers can swap their depleted batteries for fully charged ones. We are starting in Ghana, but then looking to scale across Sub-Saharan Africa and beyond. We are looking for a Data Scientist to help drive actionable insight which will improve our customers experience in how they access energy through our mobile battery network. This would include using advanced statistical and business analysis applied to a range of data points from IOT sensors, customer-driven data and a variety of other data streams. Many of the solutions will be autonomous to help Kofa run an efficient and customer biased operating system, and will serve as the foundation for the future development of AI-based interventions. We are looking for highly motivated people to help build these systems and join us on our journey to change the way people access energy, with a customer-first approach. Responsibilities Build statistical models, reports, and dashboards to support business units achieve goals Analyze large amounts of information to find patterns and solutions Use tools such as MATLAB, python, C++ to analyze data, develop algorithms and generate visualizations Design and build predictive models to help drive optimization of the network Partner with cross functional teams, develop and prioritize data science roadmaps and proactively drive projects to completion Ask key questions about the product and translate business problems and requirements into data questions Develop data processing techniques and machine learning algorithms that can support real time decision making Input and help architect the technology to enable AI

Degree in a relevant engineering program such as Computer Science / Engineering, or 3+ years experience in data science and analysis Strong python programming skills, familiarity with common python packages Strong training in math, especially statistics or other related sciences (probability, linear algebra) Demonstration of good understanding of software fundamentals including software design, algorithm development, data structures, code modularity, and maintainability Familiarity with machine learning algorithms and concepts Strong fundamentals, critical thinking, results-driven, product-oriented mindset, self-driven, good communication skills and great learning capabilities