Job Description
Work with large datasets and solve difficult analysis problems, applying advanced analytical methods. Conduct end-to-end analyses, including data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations
Build and prototype analysis and ML models pipelines iteratively to provide insights at scale. Develop comprehensive understanding of Banque Misr data structures and metrics, advocating for changes for product development and sales activity. Make actionable business recommendations with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
Research and develop analyses, forecasting and optimization methods across customer segmentation, end-user behavioral modeling, and live A/B experiments.
Manage and technically lead a data science team. Interact cross-functionally with a wide variety of leaders and teams, and work closely with Engineers and Product Managers to identify opportunities for design and to assess improvements for Banque Misr products.
Requirements
Master's degree in a quantitative discipline (e.g., Statistics, Bioinformatics, Economics) or equivalent practical experience.
6 years of experience in data analysis or related field as a Statistician, Data Scientist, Computational Biologist, or bioinformatician.
2 years of experience in people management or leadership.
Experience with statistical software (e.g., R, Python, MATLAB, pandas) and database language
Doctorate's degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).
10 years of tech industry work experience as a statistician, bioinformatician, or data scientist. Experience in statistical data analysis, such as linear models, multivariate analysis, stochastic models, and sampling methods.
4 years of leadership experience, including people management.
Applied experience with machine learning on large datasets.
Experience articulating business questions and using mathematical techniques to arrive at an answer using available data.
Ability to select the right statistical tools given a data analysis problem.
