Risk Analyst - Data-Driven FinTech (LATAM)

PayJoy

Bogotá ciudad

Presencial

COP 186.840.000 - 280.260.000

Jornada completa

Hace 6 días
Sé de los primeros/as/es en solicitar esta vacante
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Ventajas ofrecidas por este puesto de trabajo

Health for employees + family
20 days vacations
Co-working allowance
Professional development perk
Home office equipment allowance
Catered lunches

Descripción de la vacante

PayJoy is seeking a Risk Analyst to scale its LATAM point-of-sale lending portfolio. The candidate will work with data warehouses to build analyses, define actionable steps, and monitor risk KPIs across multiple countries.

You will drive profitability through data-led decisions and partner with executives, product, engineering, and GTM teams. The role emphasizes SQL mastery, proficiency in Python or R, and experience with large data sets to deliver measurable risk improvements.

Formación

  • Bachelor's degree in Finance, Economics, Mathematics, Industrial Engineering or similar.
  • 2+ years of analytical/empirical work experience.
  • Strong analytical and problem-solving skills.
  • Mastery of SQL.
  • Proficiency in Python or R.
  • Experience with large datasets and statistical methods.

Responsabilidades

  • Use SQL and Python or R to extract and manipulate data to inform recommendations.
  • Make actionable recommendations to improve outcomes based on analysis.
  • Collaborate with Data Science to implement ML/AI models that optimize portfolio outcomes.
  • Create dashboards to measure portfolio performance and test outcomes.
  • Document analyses and recommendations clearly.

Descripción del empleo

PayJoy is seeking a Risk Analyst to scale its LATAM point-of-sale lending portfolio. The candidate will work with data warehouses to build analyses, define actionable steps, and monitor risk KPIs across multiple countries.

You will drive profitability through data-led decisions and partner with executives, product, engineering, and GTM teams. The role emphasizes SQL mastery, proficiency in Python or R, and experience with large data sets to deliver measurable risk improvements.

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