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Optasia

AI-driven credit decisions for financial inclusion

Quantitative Risk Data Scientist - Fintech

Quantitative RiskConfirmed live in the last 24 hours
Full-timeAthens, Greece

About the Job

Requirements

  • A bachelor's or master's degree in Data Science, Statistics, Finance, Mathematics, or a related field.
  • Two to five years of experience in quantitative risk analysis, preferably within financial services.
  • Expertise in developing and implementing algorithmic models for revenue and risk optimization.
  • Strong proficiency in statistical modeling and experience with machine learning models.
  • Proficiency in Python or R, with extensive experience in big data risk analytics.
  • Ability to develop and implement portfolio risk assessment tools.
  • Experience working with secure code development guidelines and practices, such as OWASP and NIST.

Responsibilities

  • Design and implement algorithmic solutions for revenue optimization through credit risk analysis.
  • Deliver credit-risk insights through big data risk analytics.
  • Develop and implement portfolio risk assessment tools and procedures to monitor and manage credit risk.
  • Conduct detailed risk analysis on microloans and other financial products, optimizing risk models to improve decision-making.
  • Identify and evaluate credit risk factors using advanced computational methods on large datasets.
  • Develop predictive models, including statistical and machine learning approaches, to support risk management strategies.
  • Collaborate with data scientists and data and machine learning engineers.
  • Refine risk assessment methodologies to align with evolving market conditions.

Desired Qualifications

  • Experience in quantitative risk analysis within the financial services sector is preferred.

About the Company

Optasia

AI-driven credit decisions for financial inclusion

Optasia provides AI-driven fintech tools for intelligent credit decisions designed for Mobile Network Operators (MNOs), mobile wallet operators, and financial institutions. It uses a fully automated decisioning algorithm to evaluate data and generate millions of financing decisions in real time. The company operates on a B2B2X model, delivering real-time credit scoring, omnichannel delivery, and personalized marketing to partners who then serve end customers. Its solutions aim to enable scalable growth and broader financial inclusion for retail SME customers across multiple markets.

Company size
201-500
Company stage
IPO
Headquarters
Dubai, United Arab Emirates
Founded
2012

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