Xenon7
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Where elite tech talent meets world-class opportunities!
At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today’s most complex challenges.
Join one of Egypt’s premier financial institutions, renowned for its extensive suite of banking services, including Institutional Banking, Personal Banking, and Islamic Banking. With a global presence through over 50 branches and correspondents, we serve a diverse and dynamic clientele. As we embark on a groundbreaking digital transformation journey, we are committed to leveraging the latest technologies to establish a state-of-the-art data architecture that will redefine our performance and service delivery.
Seeking highly skilled and motivated Senior Data Scientists to join our growing team. In these roles, you will play a critical part in designing, developing, and delivering advanced data-driven solutions that drive key business decisions, while spearheading advanced analytics and machine learning initiatives across the bank.
• Lead and mentor junior data scientists, providing technical guidance, code reviews, and career development support.
• Analyze complex datasets to extract actionable insights using advanced statistical and machine learning techniques.
• Build and optimize predictive models, recommendation systems, clustering models, and time-series forecasting solutions.
• Collaborate with cross-functional teams including engineering, product, and business stakeholders to integrate data-driven solutions into production systems.
• Collaborate with MLOps and Engineering teams to automate model deployment, monitoring, and retraining pipelines using tools such as MLflow, Airflow, or Kubeflow..
• Translate analytical results into business KPIs and measure the impact of models on key financial and operational outcomes..
• Explore emerging AI capabilities, including GenAI and LLM-based solutions for document analysis, knowledge retrieval, and customer interaction..
• Write clean, maintainable code primarily in Python and SQL for data analysis, model development, and deployment.
• Communicate findings and model performance clearly to technical and non-technical stakeholders through reports and presentations.
• Ensure model governance and fairness in line with banking regulatory requirements (e.g., MRM, compliance, and audit standards).
• Strong analytical and problem-solving mindset.
• Deep expertise in machine learning algorithms and statistical methods.
• Practical experience with deep learning architectures and techniques.
• Proficient in Python and SQL for data manipulation, analysis, and model development.
• Familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras.
• Hands-on experience with predictive modeling, customer segmentation, recommendation systems, and time-series forecasting.
• Experience with time series analysis using ARIMA, LSTM, and Prophet.
• Familiarity with clustering techniques like k-means, and Gaussian Mixture Models.
• Understanding of recommendation systems including collaborative filtering, content-based, hybrid models, and deep learning-based recommenders.
• Ability to leverage machine learning algorithms like Random Forest, SVM, and XGBoost.
• Strong communication skills to present technical concepts to both technical and non-technical audiences.
• Ability to work collaboratively in cross-functional teams.
• Self-driven, highly organized, and capable of handling multiple projects simultaneously.
• Commitment to continuous learning and staying updated with advancements in data science and AI.
Originally posted on Himalayas