Remote Data Scientist - Integrated Risk & Forecasting

Plata Card; United States; Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Relocation support

Remote work globally

Healthcare Coverage

Education Budget

Wellness Budget

Vacation 20 days

Job summary

Plata Card is seeking a Data Scientist for its Integrated Risk Management team to develop risk models and analytical frameworks that support decisions across credit, financial, and operational risk. You will work on complex quantitative challenges, build predictive and diagnostic models, and partner with stakeholders to improve risk visibility and portfolio performance.

You will apply strong statistical modeling and machine learning techniques, quantify uncertainty, and collaborate with

Qualifications

• MS/PhD in statistics, CS, math, physics, econ or related field.
• 4+ years of hands-on Data Science, Quant Analytics, Risk Modeling, or similar.
• Strong stats, probability, uncertainty quantification.
• Experience with predictive models and stochastic datasets.

Responsibilities

• Develop risk models and analytical frameworks for credit, financial, and operational risk.
• Build predictive and diagnostic models; quantify uncertainty.
• Collaborate with stakeholders to improve risk visibility and decision-making across the org.
• Model distributions, confidence intervals, and risk metrics beyond point estimates.

Skills

Statistical modeling

Python

R

Uncertainty quantification

Communication

Problem-solving

Education

MS/PhD in quantitative field

Tools

Pandas

NumPy

SciPy

Statsmodels

Scikit-learn

Job description

Plata Card is seeking a Data Scientist for its Integrated Risk Management team to develop risk models and analytical frameworks that support decisions across credit, financial, and operational risk. You will work on complex quantitative challenges, build predictive and diagnostic models, and partner with stakeholders to improve risk visibility and portfolio performance.

You will apply strong statistical modeling and machine learning techniques, quantify uncertainty, and collaborate with