The Role:

As a Data Scientist/ ML Engineer you will be responsible for supporting our clients on data-driven insights and working closely with colleagues across all regions to identify cases of data science. The successful candidate will bring a good knowledge of analytics and AI and a great grasp of digital transformation.

Key Responsibilities:

• Work closely with colleagues from different departments to identify AI/ML use cases for data science that adds value to our business and our clients
• Stay up to date on the latest innovation in AI/ML/NLP space
• Support on the daily development of client deliverables and analysis of the client’s data that requires analytics and data science know-how
• Support the development of new business proposals for the clients with special focus on the analytics and AI/ML workstreams
• Supporting the digital team in several tasks such as data extraction, preparation, cleaning, analysis, visualizations, and reports generations
• Converting complicated data science and analytics aspects into simple to understand concepts presented in a PowerPoint presentation form
• Look for opportunities to use insights/datasets/code/models/libraries/etc across the clients
• Conduct research from which you’ll develop prototypes and proof of concepts using new AI/NLP libraries
• Performing analysis on requirements to identify potential gaps and dependencies and determine feasibility and time/effort required for designing, implementing, and testing individual components
• Following an internal software development process with best engineering practices
• Documenting detailed technical requirements and detailed products documentation.
• Writing good unit, integration, and end-to-end tests
• Providing technical support to clients when requested
• Monitoring and fixing issues that are reported by clients.

Required Skills & Experience:

• 2-3 years of experience in a similar role.
• Knowledge of the basics of statistics and hypothesis testing.
• Solid understanding of data science and AI/machine learning/NLP algorithms (e.g., linear regression, Doc2Vec, Transformers, etc.)
• Good understanding of system architecture and ability to design systems with ML services.
• Strong Python expertise (e.g., Jupyter Notebook, FastAPI, SciKit-Learn, Pandas, NumPy, and SciPy)
• Statsmodels for time-series data analysis and forecasting
• Solid experience in Exploratory Data Analysis (EDA) with Pandas, Plotly, or Seaborn
• Solid experience in NLP libraries: SpaCy, HuggingFace, NLTK, BERT, etc.
• Fine-tuning pre-trained models for specific use cases using PyTorch and HuggingFace.
• Solid experience in MLOps for production: Deploy ML models, continuous/active learning (e.g., prodigy) & ML observability (e.g., GCP or other platforms)
• Strong expertise and solid understanding in at least 3 of the following:
• Knowledge of headless analytics (e.g., CubeJS or Tinybird)
• Knowledge of React for front-end web applications development
• Basic understanding of web development principles and architectures.
• DevOps: Git & CI/CD, Containerization, & Deployment
• SQL Databases (e.g., BigQuery, SQL Server)
• NoSQL Databases (DynamoDB, Firebase, etc.)
• Re-usable software architecture (i.e., follows a framework)
• Data ETL & ML pipelines orchest.io or similar platforms.

Education

• A bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or other relevant disciplines (preferably with knowledge in Digital Communications) OR a portfolio of high-quality projects.

Languages

• Fluency in Arabic would be an advantage.

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