Risk Data Scientist Middle+

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

We are looking for a Risk Data Scientist.

We’re launching a new business line in Colombia and looking for someone to become the first dedicated Data Scientist in our Risk team, building the function from the ground up as part of this launch.

This is a rare opportunity to shape a function from scratch rather than optimize what someone else already built: you’ll be working with a fast-growing dataset, designing the full lifecycle of ML models used in real credit decisions, and setting the technical foundation that the rest of the Risk data science function will be built on.

Day-to-day responsibilities:

• Design, build, and own end-to-end machine learning models supporting risk decisions — from feature engineering and model development to deployment, monitoring, and retirement
• Build predicting models for adjacent functions (e.g., churn/attrition prediction on issued loans, reserve calculations)
• Establish and maintain a managed lifecycle for ML models in production — ensuring models remain stable and reliable as data volume grows
• Collaborate closely with Risk Analysts, Portfolio Managers, and Risk-tech strategy teams on model implementation

The ideal candidate:

• 3+ years of hands-on, production-level Data Science experience
• Hands-on experience across the full ML model lifecycle: development, deployment, monitoring, and decommissioning
• Experience in banking or financial services strongly preferred, with an understanding of how risk decisions are embedded in financial products
• Strong foundation in ML algorithms, feature engineering, and model development
• Proficient in Python, SQL, Airflow, Git, BI / Streamlit
• Education: Mathematics, Physics, Computer Science, or a related STEM field from a top technical university
• Comfortable working independently and owning problems end-to-end

  Our ways of working:

  • Innovative Spirit: A commitment to creativity and groundbreaking solutions
  • Honest Feedback: valuing open, transparent communication
  • Supportive Team: a strong, collaborative community
  • Celebrating Achievements: recognizing our wins together
  • High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances

  Our benefits:

  • Relocation support to one of our hubs with assistance for the employee and their family
  • Flexible work from one of our offices or remote
  • Healthcare Coverage
  • Education Budget: Language lessons, professional training and certifications
  • Wellness Budget: Mental health and fitness activity reimbursements
  • Vacation policy: 20 days of annual leave and paid sick leave