Requirements

- University Qualifications: Master’s degree in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field. - Nature and length of previous experience: At least 3 years of working experience in data science capacity within a fast-paced and complex business setting. - Specialist knowledge: Data mining tools such as Python and R, knowledge of designing KPIs and e-commerce metrics, experience working with machine learning libraries, for example, sklearn, Tensorflow and Pytorch. - Soft Skills and Personality traits: Must be able to thrive in a fast-paced, rapidly evolving environment with varying priorities, based on an agile environment. - Strong Communication Skills. - Positive attitude with an inquisitive nature. - Must be a result - oriented individual, be a self-motivated and proactive needing minimal supervision. - Must be a strategic and creative thinker, have an ability to handle multiple simultaneous projects, be highly organized able to prioritize and meet tight deadlines. - Have a keen eye for detail, have an ability to work comfortably in a group/collaborative setting, take accountability for business and team performance, have an ability to stay calm and composed in times of uncertainty and stress. Minimum Qualifications: - Have a Master’s degree in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field. - Capacity within a fast-paced and complex business setting, preferably working as a Senior Data Scientist. The candidate will also have experience working with machine learning libraries, for example, sklearn, Tensorflow and Pytorch among others. - The candidate must also have had substantial experience working on strategy or full-life cycle data science as well as experience working with data mining tools such as Python and R. A suitable candidate for this position will also have had experience in data mining and predictive modeling inclusive of linear and non-Linear regression, logistic regression, and time series analysis models. - The candidate will also have had experience working with deep learning algorithms and large data-sets as well as experience working with unstructured data and experience cleaning and manipulating data. - Knowledge of designing KPIs and e-commerce metrics.