Data Scientist "Senior/Lead"
Banque Misr Transformation office
| Company | Banque Misr Transformation office |
| Category | Data & Analytics |
| Location | New Cairo City |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Lead |
| Salary | Not stated by the employer |
| Posted | 11 Feb 2024 |
| Last verified | 3 Aug 2026 |
| Source | Employer ATS (workable) |
Description
Collaborate with product design and engineering to develop an understanding of needs Research and advise innovative statistical models for data analysis Communicate findings to business stakeholders Enable smarter business processes—and implement analytics for actionable insights Keep current with technical and industry developments Works closely with data scientist lead for identifying, specifying and prioritizing the deliverables for each business use-case As a Data Scientist, you will be working in an agile team at the forefront of shaping Customers’ experience using machine learning and predictive statistical modeling. solve data problems and develop innovative data solutions using Disruptive mindset Designs, deploys and evaluate predictive models and advanced algorithms to drive business decisions Contributes in data architecture decisions and collaborate with technology teams to implement model. Performs data processing including statistical analysis, variable selection, and dimensionality reduction Requirements ▪ Bachelor degree in Economics, Computer Science, Engineering, Statistics, Mathematics, Physics, Operations Research, or related discipline with excellent academic record. ▪ Solid understanding of foundational statistics concepts and ML algorithms: linear/logistic regression, random forest, boosting, neural networks ▪ Experience in at least one of the following languages: Python, Java, Scala, R.(Python is preferred) ▪ SQL Fluent ▪ Good communication skills, with ability to work cross functional teams to translate business issues into potential analytics solutions ▪ Master in computer science or statistics ▪ Experience with working on large data sets, especially with Hadoop and Spark. ▪ Experience with distributed databases such as Hive, Impala, Redis, etc