{"id":3722874,"url":"https://alion.io/job/bbva-data-scientist-riesgos","title":"Data Scientist - Riesgos","company":{"id":41135,"name":"BBVA","domain":"bbva.com","url":"https://alion.io/company/news-bbva","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":90,"open_postings":80,"ghost_share":0,"stale_share":0.6,"repost_share":0.013,"time_to_fill_p50_days":13,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Buenos Aires, Argentina"],"countries":["AR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"CAPA","optional":false},{"name":"NumPy","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Statsmodels","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-03T00:00:00Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-07T04:08:21Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Excited to grow your career?\nBBVA is a global company with more than 160 years of history that operates in more than 25 countries where we serve more than 80 million customers. We are more than 121,000 professionals working in multidisciplinary teams with profiles as diverse as financiers, legal experts, data scientists, developers, engineers and designers.\nAbout the job:\nNos encontramos en la búsqueda de un/a Data Scientist para formar parte de nuestro equipo de IFRS9/CORE dentro del CoE de Advanced Analytics de Riesgos. La persona seleccionada será responsable de implementar metodologías, calibrar parámetros regulatorios para provisiones y capital, y desarrollar modelos de riesgos estructurales con alto rigor cuantitativo.\nResponsabilidades:\nImplementar metodologías analíticas y calibrar parámetros cuantitativos para provisiones y capital regulatorio y económico.\nDesarrollar, actualizar y calibrar modelos cuantitativos de riesgos estructurales (modelos de prepagos, depósitos y partidas off-balance) para la gestión de liquidez y balance.\nColaborar activamente en proyectos estratégicos como NGA EBA, enfocado en el desarrollo y adaptación de la definición de default.\nConstruir pipelines de extracción y análisis de datos eficientes sobre entornos analíticos cloud utilizando SQL y Python.\nDocumentar técnicamente los modelos y justificar resultados ante las distintas capas de control interno, auditorías y organismos supervisores (BCRA, EBA).\nInteractuar de forma fluida con interlocutores de Finanzas, Contabilidad, Riesgos Financieros y equipos globales de Holding para el entendimiento integral de las carteras.\nImpulsar la optimización, eficiencia y automatización de los procesos de calibración.\nRequisitos:\nGraduados o estudiantes avanzados de carreras como Actuario, Economía, Matemática, Estadística, Ciencias de Datos o afines.\nExperiencia laboral comprobable de 2 años en adelante en modelado cuantitativo, análisis de datos o analítica de riesgos dentro del sector bancario/financiero o en proyectos de consultoría afines.\nDominio excluyente de SQL y Python aplicado al análisis de datos y modelado estadístico.\nNivel de inglés intermedio (capacidad para comprender documentación técnica, normativas internacionales y participar de instancias corporativas).\nValoraremos conocimientos previos en normativa IFRS 9 (parámetros PD, LGD, EAD) y/o modelos de riesgos estructurales/financieros.\nSkills:\n Hard Skills: SQL avanzado, Python (pandas, numpy, scikit-learn/statsmodels), modelado estadístico y econométrico, entornos cloud/Big Data (AWS Athena/PySpark valorado), normativas IFRS 9 / EBA (deseable).\nSoft Skills: Capacidad analítica y atención al detalle, orden y disciplina metodológica en documentación, adaptabilidad a la rotación de proyectos, excelentes relaciones interpersonales y comunicación asertiva.\n¿Qué ofrecemos?\nFormar parte de una entidad bancaria de prestigio, con oportunidades de desarrollo profesional.\nCapacitación constante en procesos, herramientas y atención al cliente.\nExcelente clima de trabajo y beneficios corporativos.\nSkills:\nData Analysis, Interest Rate Models, Interest Rate Risk, Logistic Regression Analysis, Loss Given Default, Probability of Default, 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