Senior Risk Data Scientist — Build ML Risk from Scratch

Plata Card; Colombia; Híbrido; COP 90.000.000 - 160.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Relocation support

Flexible work from offices or remote

Healthcare Coverage

Education Budget

Wellness Budget

Vacation policy: 20 days

Descripción de la vacante

Plata Card is launching a new risk data science function in Colombia and seeks the first dedicated Data Scientist to shape the function from scratch. You will design, build, and deploy end-to-end ML models for risk decisions, monitor performance, and collaborate with Risk Analysts and Portfolio Managers.

The role emphasizes hands-on, production-level DS work with a strong foundation in ML, feature engineering, and model development, using Python, SQL, Airflow, Git, and BI/Streamlit.

Formación

• 3+ years of production-level Data Science experience.
• Experience across full ML model lifecycle: development, deployment, monitoring, decommissioning.
• Experience in banking or financial services preferred; understanding risk in financial products.
• Strong foundation in ML algorithms, feature engineering, and model development.

Responsabilidades

• Design, build, and own end-to-end ML models supporting risk decisions from feature engineering to deployment and monitoring.
• Build predicting models for related areas (e.g., churn/attrition, reserve calculations).
• Establish and manage a lifecycle for ML models in production with data growth considerations.
• Collaborate with Risk Analysts, Portfolio Managers, and Risk-tech strategy teams on model implementation.

Conocimientos

Independent work

Analytical thinking

Communication

Educación

Mathematics

Physics

Computer Science

Herramientas

Airflow

Git

BI/Streamlit

Python

SQL

Descripción del empleo

Plata Card is launching a new risk data science function in Colombia and seeks the first dedicated Data Scientist to shape the function from scratch. You will design, build, and deploy end-to-end ML models for risk decisions, monitor performance, and collaborate with Risk Analysts and Portfolio Managers.

The role emphasizes hands-on, production-level DS work with a strong foundation in ML, feature engineering, and model development, using Python, SQL, Airflow, Git, and BI/Streamlit.