Senior Data Scientist

Company Description

Egis is an international player active in architecture, consulting, construction engineering and mobility services. We create and operate intelligent infrastructures and buildings that respond to the climate emergency and contribute to more balanced, sustainable and resilient territorial development. Operating in 100 countries, Egis puts the expertise of its 19,500 employees at the service of its clients and develops cutting-edge innovations accessible to all projects. Through its wide range of activities, Egis is a key player in the collective organisation of society and the living environment of citizens all over the world.

With 3,500 employees across 8 countries in the Middle East, Egis has delivered over 700 complex development projects, stimulating economic growth and enhancing quality of life. Ranked among the top ten firms in the Middle East by Engineering News Record (ENR), Egis is committed to sustainable development. The Group’s operations in the Middle East are built on strategic acquisitions and a deep understanding of local market conditions. Egis’ long history of providing comprehensive engineering, consulting, and project management services makes it a trusted partner for regional governments, investors, and developers.

Job Description

We are looking for a highly experienced Senior Data Scientist with strong expertise in data mining, machine learning, and deep learning techniques. The ideal candidate will have a solid academic background and at least 5 years of industry experience applying advanced analytics to solve real-world problems. You should be fluent in Python and skilled with libraries like TensorFlow and Scikit-learn, capable of designing and deploying complex models that generate business value.

1. Key Responsibilities:

• Design, develop, and implement machine learning and deep learning models for classification, regression, clustering, and other tasks.
• Perform data mining to uncover hidden patterns, anomalies, and correlations in large-scale datasets.
• Build end-to-end pipelines for data preprocessing, model training, validation, and deployment.
• Collaborate with data engineers, product managers, and business analysts to translate problems into actionable data science solutions.
• Evaluate model performance using appropriate metrics and fine-tune for optimal results.
• Communicate complex analytical results and insights to both technical and non-technical stakeholders.
• Stay updated with the latest research and advancements in AI, deep learning, and data science.

Qualifications

Required Qualifications:

• Master’s degree in Computer Science, Data Science, Statistics, or a related field.
• 5+ years of professional experience in data science or machine learning.
• Strong knowledge of data mining and statistical analysis techniques.
• Expertise in Python with deep hands-on experience in TensorFlow, Scikit-learn, and other ML/DL libraries (e.g., Keras, PyTorch).
• Solid foundation in deep learning techniques, including CNNs, RNNs, GANs, and attention mechanisms.
• Proficiency with data visualization tools (Matplotlib, Seaborn, Plotly) and data manipulation libraries (Pandas, NumPy).
• Strong communication and problem-solving skills.