{"id":4186656,"url":"https://alion.io/job/avenga-senior-data-scientist","title":"Senior Data Scientist","company":{"id":181252,"name":"Avenga","domain":"avenga.com","url":"https://alion.io/company/avenga","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Teamtailor","truth_index":{"grade":"B","score":78,"open_postings":29,"ghost_share":0,"stale_share":0.862,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mexico"],"countries":["MX"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Keras","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-11-12T16:04:55Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-12T18:29:29Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Avenga is an international engineering firm helping businesses operate with AI at the core. With 6,000+ experts worldwide, we combine engineering expertise with AI-native thinking to turn ambitious ideas into real-world impact across industries, technologies, and markets. \nAt the core of the role\nWe are actively seeking an experienced AI Solutions Architect / Senior AI & Machine Learning Engineer to join a technology-driven project focused on designing and implementing advanced Artificial Intelligence and Data Science solutions.\nIn this role, you will be responsible for defining scalable AI and Machine Learning architectures, developing and optimizing models, and deploying them into production environments. You will work across the full AI lifecycle, from data preparation, statistical modeling, and experimentation to production deployment, monitoring, and optimization.\nYou will collaborate with technical and business stakeholders to transform complex requirements into robust, scalable AI solutions, working with modern cloud and Big Data ecosystems. The role offers the opportunity to work with traditional Machine Learning techniques as well as emerging technologies such as Large Language Models (LLMs) and Prompt Engineering.\nCore skills you’ll bring\nStrong experience designing and implementingArtificial Intelligence, Machine Learning, and Data Science architectures.\n\nAdvanced knowledge of Machine Learning algorithms, including Decision Trees, Random Forest, SVM, K-Means, Naive Bayes, KNN, and Neural Networks.\n\nStrong hands-on development experience with Python and Shell Scripting.\n\nExperience with ML frameworks and libraries such as TensorFlow, PyTorch, Keras, and Scikit-learn.\n\nHands-on experience working with Large Language Models (LLMs) and Prompt Engineering.\n\nStrong knowledge of advanced statistical techniques, including statistical modeling, clustering, and predictive analytics.\n\nExperience developing and optimizing SQL queries.\n\nExperience defining data quality, control, validation, and assurance mechanisms.\n\nExperience deploying Machine Learning models into production environments using Docker and Kubernetes.\n\nExperience with Big Data and cloud ecosystems, such as Cloudera, AWS, Azure, or GCP.\n\nKnowledge of real-time and batch data processing.\n\nExperience with advanced model optimization and hyperparameter tuning.\n\nAvailability to work under a hybrid model, attending the office three days per week.\n\nAvailability to travel when required by business or operational needs.\n\nNice-to-have\nExperience designing end-to-end AI solutions across complex or large-scale environments.\n\nExposure to multiple cloud platforms, including AWS, Microsoft Azure, or Google Cloud Platform (GCP).\n\nExperience integrating LLMs and Generative AI solutions into enterprise applications or business workflows.\n\nKnowledge of MLOps practices and model lifecycle management.\n\nExperience working with large-scale or distributed data environments such as Cloudera.\n\nStrong communication skills and experience collaborating with multidisciplinary technical and business teams.\n\nThe impact you'll create\nDesign and implement scalable AI, Machine Learning, and Data Science architectures aligned with business and technical requirements.\n\nDevelop, train, validate, optimize, and deploy Machine Learning models into production environments.\n\nBuild AI solutions leveraging both traditional Machine Learning algorithms and Large Language Models.\n\nDefine reliable data quality, validation, and control mechanisms to support AI initiatives.\n\nOptimize model performance through advanced statistical techniques and hyperparameter tuning.\n\nSupport real-time and batch data processing scenarios across cloud and Big Data environments.\n\nCollaborate with engineering, data, and business stakeholders to translate complex challenges into production-ready AI solutions.\n\nContribute to the continuous improvement and evolution of the organization's Artificial Intelligence capabilities.\n\nPeople are at the core of Avenga. We provide equal opportunities regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. 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