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Mid Data Scientist

Roles & Responsibilities

  • Degree in a quantitative field (e.g., Actuary, Mathematics, Physics, Statistics, Computer Science, or related)
  • At least 2 years of Data Science experience with machine learning models
  • Proficiency in SQL and production-level Python programming with Pandas; experience with AWS SageMaker
  • Strong statistics fundamentals (e.g., distributions, generalized linear models, A/B testing, experiment design, simulation) and advanced English

Requirements:

  • Design, develop, and implement machine learning models and algorithms for underwriting and customer management
  • Improve existing models through experiments, rigorous testing, validation, and benchmarking to ensure accuracy and reliability
  • Maintain and iterate on models in production within risk management workflows
  • Apply advanced analytical methods to solve complex business challenges and present insights with charts/graphs to non-technical stakeholders

Job description

Join the Fintech revolution and build the future of finance in Mexico!


Who are we?

We are the leading financial technology company in Mexico, empowering more than 70,000 clients to achieve their dreams. Our mission is to empower the country's small and medium-sized enterprises with innovative solutions (financing, credit card and payments) to overcome their challenges and turn them into the engines of economic growth. We aspire to be the ideal ally of entrepreneurs, contributing to the development of the community, the country and the planet.

Your Mission, Should You Choose to Accept It:

The primary goal of the Data Scientist in Risk Management is to develop, implement, and maintain machine learning models and algorithms to enhance underwriting processes and customer management strategies. This role involves continuous improvement and experimentation with models. This role involves working closely with the Lead or Manager Data Scientist, as the middle position is not completely independent and requires assistance and guidance.

  • Model Development and Implementation: Design, develop, and implement machine learning models and algorithms for underwriting and customer management.
  • Model improvement: Conduct experiments to enhance existing models, ensuring their accuracy and reliability through rigorous testing, validation, and benchmarking.
  • Analytics and Communication: Apply advanced analytical methodologies to solve complex business challenges, presenting insights through charts and graphs, and communicating findings to non-technical stakeholders.


What We're Looking For:

  • Basic qualification: Degree in a quantitative discipline (e.g., Actuary, Mathematics, Physics, Statistics, Computer Science, or related field).
  • Proven experience in Data Science (at least 2 years).
  • Knowledge and experience with Machine Learning models. Knowledge of SQL. Experience in production programming in Python and Pandas library. AWS SageMaker
  • Statistics fundamentals: most common distributions, generalized linear models, hierarchical models (desirable), A/B testing, bootstrap, experiment design, simulation.
  • Advanced english (must).


What We Offer:

  • A dynamic and collaborative work environment where you can develop your full potential.
  • Opportunities to learn and grow professionally using cutting-edge technologies.
  • A passionate and talented team with whom you can share knowledge and experiences.
  • A competitive compensation package and attractive benefits.
  • The opportunity to positively impact the lives of thousands of people and contribute to the development of the country.

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