{"id":1805846,"url":"https://alion.io/job/capgemini-senior-data-scientist-ai-ml-engineer","title":"Senior Data Scientist - AI & ML Engineer","company":{"id":145,"name":"Capgemini","domain":"capgemini.com","url":"https://alion.io/company/capgemini","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":81,"open_postings":1748,"ghost_share":0,"stale_share":0.761,"repost_share":0.001,"time_to_fill_p50_days":27,"computed_at":"2026-10-12T06:55:09Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","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":56000,"max_usd":143000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1986},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-09-24T11:08:19Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-10-12T13:26:34Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"description":"About Capgemini\nCapgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2024 global revenues of €22.1 billion.\nJob Description:\nDesign and implement Agentic AI solutions and applications.\nLead the end-to-end lifecycle of machine learning and data science delivery engagements, from data ingestion and feature engineering to model training, evaluation, and deployment.\nMonitor model performance and implement retraining strategies to ensure long-term accuracy and relevance.\nArchitect and optimize scalable data pipelines and cloud-based infrastructures (Azure, AWS, GCP) to support ML workloads.\nCollaborate with data engineers to ensure robust data preprocessing, transformation, and storage strategies.\nDevelop and maintain CI/CD pipelines tailored for ML workflows, including automated testing, model versioning, and deployment.\nIntegrate monitoring and alerting systems to track model drift, data quality, and system performance.\nWork closely with cross-functional teams including data scientists, product managers, and business stakeholders to translate business needs into technical solutions.\nMentor junior engineers and contribute to knowledge sharing and best practices across the team.\nJob Requirements:\n6-10 years of experience working with complex datasets and solving real-world business problems using AI\nProven track record of deploying and maintaining ML models in production environments and delivering AI solution architecture.\nStrong proficiency in Python, data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and agentic application development libraries (e.g. LangChain, LangGraph).\nStrong command of SQL and experience with large-scale data processing tools (e.g., Spark, Pandas).\nDeep understanding of cloud platforms (Azure, AWS, GCP) and their ML services.\nSkilled in MLOps practices including CI/CD, containerization (e.g. Docker), and orchestration (Kubernetes).\nStrong command of Git and collaborative development workflows.\nExcellent written and verbal communication skills, capable of conveying complex concepts to a variety of audiences.\nFluent in Arabic & English, both spoken and written (German is a plus!)\nAble to listen to and understand customer needs and articulate them as technical requirements to the team.\nStrong problem-solving abilities and attention to detail.\nStrategic thinking with the ability to align data science initiatives with business objectives.\nStrong leadership and team management skills with the ability to inspire and motivate.\nAbility to work collaboratively in a team environment.\nSelf-motivated with a strong growth mindset.","description_format":"text","description_chars":3318,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"German","level":"All levels","optional":true},{"language":"Arabic","level":"Advanced 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