Data Scientist At Giza Systems
Selecting features, building and optimizing classifiers using machine learning techniques
Data mining using state-of-the-art methods
Extending company’s / customers’ data with third party sources of information when needed
Enhancing data collection procedures to include information that is relevant for building analytic
Processing, cleansing, and verifying the integrity of data used for analysis
Doing ad-hoc analysis and presenting results in a clear manner
Creating automated anomaly detection systems and constant tracking of its performance
Prepares / Reviews low-level design.
Develops / reviews software application code making sure of conformance of coding standards and
Preparing unit test cases and writing unit test code.
Fixing software bugs reported by internal and external testing teams.
Fixing bugs in open-source software supported by the company and software products developed by
Accountable for providing high quality software products and service
Self-starter with a proactive attitude
Excellent written and verbal communication skills for coordinating across teams.
Individual contributor able to work effectively across different teams
Excellent organizational, time management, and presentation skills.
Ability to communicate effectively with peers, management, & business groups
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial
neural networks, etc.) and their real-world advantages/drawbacks
Excellent understanding of machine learning and deep learning techniques, such as Naive Bayes, SVM,
Random Forests, CNNs, RNNs, GANs, Attention Models, etc.
Excellent Coding Skills in Python is required and other coding knowledge and experience with other
languages like Java, and R is highly desirable.
Excellence at using common python data science packages like Scikit-Learn / NumPy / SciPy/ Matplotlib
Design and build Machine Learning and Deep Learning pipelines to solve business problems.
Experience with data visualization tools, such as Plotly Dash, Tableau, PowerBI etc.
Experience in using query languages such as SQL.
Good applied statistical skills, such as distributions, statistical testing, regression, etc.
Proven hands-on experience in dealing with a variety of machine learning tasks and data types
including tabular, time-series, image, and sequential data.
Apache Spark ML
Bachelor’s degree or equivalent experience. Preferred Computer science or engineering.
Employer (Private Sector)
Years of Experience
Min: 0 Max: 2