{"id":30910,"url":"https://alion.io/job/inetum-data-scientist","title":"Data Scientist","company":{"id":3561,"name":"Inetum","domain":"inetum.com","url":"https://alion.io/company/inetum","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":83,"open_postings":574,"ghost_share":0,"stale_share":0.695,"repost_share":0,"time_to_fill_p50_days":33,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mexico City, Mexico"],"countries":["MX"],"hiring_countries":["MX"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":35000,"max_usd":91000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2324},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Azure","optional":false},{"name":"Git","optional":false},{"name":"LightGBM","optional":false},{"name":"MLFlow","optional":false},{"name":"Pandas","optional":false},{"name":"Polars","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SciPy","optional":false},{"name":"SQL","optional":false},{"name":"Statsmodels","optional":false},{"name":"TensorFlow","optional":false},{"name":"XGBoost","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-07-22T15:19:46Z","employer_posted_date":"2026-07-22","last_verified_at":"2026-10-18T00:39:17Z","board_verified":true,"closed_at":null,"days_open":87,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":86},"description":"Inetum es un grupo internacional de consultoría digital ágil. En la era post-transformación digital, nuestro propósito es permitir que cada una de las más de 27,000 personas que forman parte de nuestro equipo se renueve continuamente, viviendo de forma positiva su propio flow digital.\nCon presencia en 26 países, promovemos trayectorias profesionales flexibles, innovación local y un equilibrio saludable entre la vida personal y profesional. Además, Inetum ha sido reconocida como Top Employer, certificación que avala nuestro compromiso con el bienestar, el desarrollo profesional y la excelencia en la gestión del talento.\nCompromiso con la igualdad\nEn Inetum, promovemos un entorno de trabajo inclusivo y equitativo. Se tendrán en cuenta todos los candidatos, independientemente de su género, identidad, orientación sexual, edad, origen étnico, discapacidad u otras condiciones. Las decisiones de contratación se basan únicamente en las habilidades, competencias y valores alineados con nuestra cultura organizativa.\nNota de transparencia:\nEn nuestro proceso de selección utilizamos herramientas deinteligencia artificial para realizar un prefiltrado de perfiles. Estas herramientas se emplean únicamente como apoyo para el análisis y no toman decisiones de contratación, las cuales siempre son validadas por nuestro equipo de reclutamiento.\nSi consideras que tu postulación fue evaluada de manera incorrecta, puedes escribirnos a:\n\n We are looking for a Senior Data Scientist with a solid statistical background and\npractical experience in data science projects in business environments. The\ncandidate must be able to frame complex problems as modeling problems,\nexecute rigorous research cycles, and deliver reproducible solutions that can be\nintegrated by engineering teams.\nThis role operates in close collaboration with an ML Engineering team. The\ncandidate is expected to have clear judgment about their responsibilities within\nthat ecosystem and the discipline to work with software engineering standards,\nnot just analysis standards.\n What We Are Looking For\nTechnical Fundamentals\nAdvanced mastery of Python as the primary and sole development language.\nSolid knowledge of data science and ML libraries: Scikit-Learn , XGBoost ,\nLightGBM , Pandas , Polars , Statsmodels , SciPy .\nExperience with deep learning models ( TensorFlow or PyTorch ) when the\nproblem justifies it.\nAbility to work with data at scale: advanced SQL, PySpark for exploration\nand transformation.\nAccess to and handling of data in cloud environments (GCS, Azure Blob\nStorage).\nStatistical Rigor\nExperimental design and hypothesis testing applied to business problems.\nUnderstanding of causality: not just correlation but the ability to distinguish and\napply appropriate techniques.\nRobust model validation: beyond accuracy, business metrics, bias analysis, and\nsubgroup behavior.\nDevelopment Discipline\nProfessional use of Git as part of the usual workflow, not as a formality at\ndelivery time.\nOrganized and modular Python code: the candidate must produce deliverable\ncode, not just exploration notebooks.\nFamiliarity with experiment tracking tools (MLflow or equivalent) for\nexperiment traceability.\nAbility to document models in a structured way: what it solves, with what data,\nwith what limitations.\nExperience working under team standards: secure credential handling, data\nversioning, project structure.\nJudgment on AI\nResponsible use of generative AI tools as assistants: with the critical ability to\nreview and validate what they produce.\nJudgment to evaluate when agent systems or LLMs are the right tool and when\nthey are not.\nRecommended Experience\nNotes for the Search\nThe selection process includes a practical technical evaluation and review\nof the candidate’s previous work.\nReasoning ability and judgment will be valued over code production speed.\nWe are not looking for profiles who use tools without understanding them: we\nare looking for candidates who can justify their technical and statistical\ndecisions.\nThe candidate will work under engineering standards defined by the team -\nwillingness and ability to adopt them from the start of any project is expected.\nMore than 5 years in data science, statistical analysis, or applied research roles.\nDocumentable end-to-end projects: from problem definition to delivery of a\nvalidated model.\nExperience working with engineering teams (ML Engineers, Data Engineers) in\nagile environments.\nWork history in real code repositories (a shareable portfolio will be valued).\nAcademic Background\nMaster’s or Doctoral degree in: Mathematics, Statistics, Actuarial Science,\nPhysics, Computer Science, or related fields.\nExperience in academic or applied research is a differentiator.\n Lo que ofrecemos\nProgramas de formación continua y certificaciones.\nAcceso a plataformas de aprendizaje y desarrollo profesional.\nCultura de innovación y colaboración.\nProgramas de bienestar físico y emocional.\nOportunidades de crecimiento en proyectos internacionales.\nReconocimiento y recompensas por desempeño. \n Sueldo base\n Prestaciones superiores a las de la ley\nSeguro de vida \nSeguro de Gastos Médicos Mayores\nVales de despensa\nEsquema 100% nómina","description_format":"text","description_chars":5207,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[{"language":"Spanish","level":"All levels","optional":false}]},"benefits":[],"hiring_locations":[{"name":"Mexico","iso":"MX","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","Managed IT Services (MSP)","Systems 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