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Job Description

Mid Level Data Scientist /Machine Learning Engineer


El Gouna, Red Sea, Housing facility is provided


We seek aMid-Level Data Scientist and AI/ML Engineer focusing on time series, NLP, TensorFlow, and data engineering.You’ll play a crucial role in developing end-to-end solutions that leverage structured and unstructured data. You’ll be responsible for building and deploying models and gathering, processing, and researching data sources to fuel these models. This hands-on, cross-functional role is ideal for someone eager to contribute to the full data and AI pipeline within a startup environment.


Key Responsibilities:


Data Gathering & Extraction:Proactively identify, gather, and extract data from diverse sources, including public and private datasets, APIs, and web scraping as needed. Effectively handle both structured and unstructured data.


  • Collect sales, shopper, store, and product data for model training

Data Engineering & Pipeline Development:Collaborate with Data Engineers in designing, building, and maintaining efficient data pipelines to process and manage high-quality datasets for machine learning.


  • Automate data gathering and data pre-processing

Time Series Analysis & Forecasting:Build and implement time series forecasting models using TensorFlow and related libraries, enabling predictive insights from time-dependent data.


  • Build sales-based predictive models to aid our products

NLP Solution Development:Develop NLP models using TensorFlow, Keras, and NLP libraries (e.g., TensorFlow Text, Hugging Face Transformers) for tasks like sentiment analysis, text classification, and named entity recognition.


  • Build NLP-based predictive models to aid our products

End-to-End Model Deployment:Collaborate in deploying and optimizing machine learning models, leveraging TensorFlow Serving and TFX for production-ready solutions. Ensure models are robust, scalable, and monitored effectively.


  • Collaborate with software engineers in the preparation and deployment & release of predictive models

Cross-Functional Collaboration:Partner with product, engineering, and design teams to align on data and model requirements, ensuring seamless integration within our product.


Required Skills & Qualifications:


Experience & Skills:3+ years in a data science, machine learning, or data engineering role, with experience in time series, NLP, and data extraction. Startup or fast-paced environment experience is a plus.


Data Engineering Expertise:Strong data engineering skills, including data extraction, data wrangling, and pipeline building. Familiarity with Apache Spark, SQL, and ETL processes.


TensorFlow & Machine Learning:Proficiency with the TensorFlow stack (TensorFlow, Keras, TensorFlow Data Services, TensorFlow Serving, TFX) and libraries for time series and NLP modeling.


Data Research & Sourcing:Proven experience researching and identifying relevant public and private datasets, APIs, and open data sources.


Deployment & Cloud Experience:Hands-on experience deploying models in production using Docker, Kubernetes, and cloud platforms like AWS, GCP, or Azure.


Communication & Visualization Skills:Ability to create clear visualizations and effectively communicate insights and model results to stakeholders with varying levels of technical understanding.


Curiosity & Adaptability:Eager to learn, resourceful, and proactive in finding new data sources, tools, and methods to enhance our AI capabilities.


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