{"id":2629911,"url":"https://alion.io/job/vertex-technologies-middle-data-scientist","title":"Middle Data Scientist","company":{"id":3882190,"name":"Vertex Technologies","domain":"vertextech-eg.com","url":"https://alion.io/company/vertextech-eg","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cairo, Egypt"],"countries":["EG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":46000,"max_usd":125000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":865},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Docker","optional":false},{"name":"FAISS","optional":false},{"name":"GitHub","optional":false},{"name":"GitLab CI","optional":false},{"name":"Keras","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LightGBM","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"OpenAI","optional":false},{"name":"Pandas","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false},{"name":"XGBoost","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-15T15:39:00Z","employer_posted_date":null,"last_verified_at":"2026-10-15T15:39:00Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are currently seeking a skilled and experienced Data Scientist to join our team. As a Data Scientist, you will be responsible for experiments with datasets searching for useful insights and features, maintaining data pipelines and training machine learning algorithms, and visualizing results.\n Main goals and responsibilities:Be a proactive team worker;\n\nCollaborate with the team to implement new features to support the growing data needs;\n\nBuild, maintain, and deploy DS and ML pipelines, including data retrieval, preprocessing, feature engineering, training, and inferencing the models, analyzing and visualizing the results;\n\nBuild, maintain and deploy LLM-powered systems and agent pipelines, including prompt engineering, tool and API integration, memory and context management, inference orchestration, and evaluation of model outputs;\n\nShare knowledge with other teams on various data science or project-related topics;\n\nCollaborate with the team to decide on which tools and strategies to use within specific scenarios.\n\n What We Offer:\nLong-term career stability with a competitive salary paid in USD.\n\nConditions for steady career development.\n\nDevelopment supported by dedicated mentors and a variety of programs focused on expertise and innovation.\n\nPrivate medical insurance provided after successful completion of the probationary period\n\nA well-equipped and cozy office supports comfort and productivity across all project stages.\n\nWelcoming atmosphere and a friendly corporate culture.\n\nRequirements\nRequired:English level upper intermediate+;\n\nGood mathematical and statistical background, tensor calculus;\n\nGood knowledge of databases such as Postgres, MongoDB, and SQL;\n\nPython language including practical experience with Scikit-learn, Numpy, Pandas, and Matplot libraries;\n\nExperience with gradient boosting algorithms (XGBoost or LightGBM);\n\nFamiliarity with LLM orchestration tools (e.g., LangChain, LangGraph);\n\nExperience using or integrating with cloud LLM APIs (e.g., OpenAI, Claude, Amazon Bedrock, Vertex AI);\n\nHands-on experience with Retrieval-Augmented Generation (RAG) pipelines and vector databases (e.g., pgvector, FAISS, Weaviate, Pinecone);\n\nPractical experience with prompt engineering techniques, agentic tools and workflows;\n\nAt least 1 framework to build and train neural networks (TensorFlow/Keras, PyTorch), a good understanding of neural networks architectures, and how-tos;\n\nCommercial experience with classic machine learning and deep learning, including NLP and CV models like Bert, Resnet;\n\nPractical skills in building en-to-end ML training pipelines (data load, preprocess, train, inference), as well as GitHub / GitLab CI/CD flows;\n\nDocker or Kubernetes platform;\n\nWork experience as a Data Scientist more than 2 years.\n\nNice to have:Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP);\n\nAbility to work with Spark, 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