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Open nowFirst seen 5 days ago

Especialista de Datos (Crédito y Cobranza)

Externa Talent Hunters402 open roles

Where
Cuenca, Ecuador
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Your applicationOpen nowEspecialista de Datos (Crédito y Cobranza)Externa Talent Hunters · Cuenca, Ecuador

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Externa Talent Hunters's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: first seen 5 days ago

The posting

Misión del cargo:

Transformar los datos de la cartera de crédito en inteligencia accionable que permita optimizar las decisiones de originación, fortalecer las estrategias de cobranza y mejorar la gestión del riesgo crediticio, mediante el desarrollo de modelos analíticos, herramientas estadísticas y recomendaciones basadas en datos que aporten a los objetivos del negocio.

Nivel de instrucción:

Título de Tercer nivel en: Ingeniería en Sistemas, Ingeniería Industrial, Economía, Estadística / Matemáticas o carreras afines

Deseable:

Postgrado, diplomados o certificaciones en Data Science, Machine Learning o Riesgo Crediticio.

Cursos especializados en plataformas como Coursera, DataCamp, edX o similares.

Experiencia:

Experiencia de 1 a 3 años en análisis de datos, preferentemente en áreas de crédito, cobranza, banca, fintech, retail financiero o empresas con cartera propia.

Lugar de trabajo: Cuenca

Competencias:

- Pensamiento analítico

- Comunicación efectiva

- Proactividad

- Orientación al detalle

- Trabajo en equipo

- Gestión del tiempo

Conocimientos técnicos requeridos.

- Python o R para análisis estadístico y modelamiento predictivo.

- SQL para consulta y procesamiento de bases de datos relacionales.

- Estadística aplicada y modelos predictivos.

- Machine Learning aplicado al negocio.

- Desarrollo de scorecards de crédito.

- Metodologías WOE, IV, Gini, KS y PSI.

- Vintage Analysis (análisis de cosechas).

- Matrices de transición de mora (Roll Rates)

- Modelos de propensión al pago.

- Segmentación de clientes y análisis de riesgo.

- Procesos ETL (extracción, transformación y carga de datos).

- Desarrollo de dashboards en Power BI.

- Excel avanzado.

- Calidad y validación de datos.

Funciones a desempeñar:

- Construir y mantener scorecards de originación de crédito al consumidor.

- Analizar variables predictoras relacionadas con riesgo de mora y comportamiento de clientes.

- Realizar análisis de cosechas (Vintage Analysis) para evaluar el desempeño de la cartera.

- Proponer ajustes en políticas de aprobación, cupos, plazos y condiciones de crédito basados en evidencia analítica.

- Desarrollar matrices de transición de mora (Roll Rates) para monitorear el comportamiento de la cartera.

- Segmentar clientes según nivel de riesgo y probabilidad de recuperación.

- Desarrollar modelos de propensión al pago que permitan priorizar estrategias de cobranza.

- Analizar la efectividad y costo de los distintos canales de recuperación.

- Generar reportes periódicos sobre indicadores de cartera, mora, productos y segmentos.

- Diseñar y mantener dashboards ejecutivos para la Gerencia de Crédito y Dirección General.

- Automatizar procesos de extracción y procesamiento de información.

- Elaborar presentaciones con hallazgos, conclusiones y recomendaciones estratégicas.

- Validar la integridad y consistencia de las bases de datos de crédito.

- Documentar metodologías, supuestos y resultados de los modelos desarrollados.

- Trabajar en conjunto con el área de Sistemas para mejorar la arquitectura y disponibilidad de los datos.

Sueldo: $1300 - $1600 fijos

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