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    Senior Data Scientist - Mexico City, México - Konfío

    Konfío
    Konfío Mexico City, México

    hace 3 horas

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    A De jornada completa
    Descripción

    Who We Are

    We are the financial technology company in Mexico that has helped more than 70k customers to make their plans come true.

    Our purpose is to support small and medium enterprises in the country to fulfill their dreams, through our solutions (financing, credit card and payments) to help solve their main problems, seeking to be the best ally of entrepreneurs, contributing to the community, the country and the world.

    About the Data Science Team

    We are a high-performance team committed to follow best practices, both in modeling and programming, to ensure that our deliverables are of the highest quality.

    Our mission at Konfio is to work intelligently, utilizing data, statistics, and models to innovate while simultaneously generating value for Konfio. As part of the team, you will be able to leverage your knowledge and creativity to contribute to this mission, and at the same time, you will be improving and learning, since we are independent professionals but share knowledge and collaborate with each other.

    Currently we have robust processes, but that doesn't mean we can't improve them, so proactivity and experimentation are really encouraged/very welcome.

    About the Role

    We are particularly interested in individuals who consistently seek improvements and generate innovative ideas. And we expect them to be very independent, capable of proposing solutions and requiring little guidance from her or his leader.

    We will give particular emphasis in our selection process for those candidates who not only possess technical expertise but also stand out in effective communication and can transmit complex technical concepts with clarity. This skill is essential for ensuring successful project outcomes and assure a clear understanding inside and outside the team.

    Additionally, the ideal candidate should be an excellent team player and actively contribute to promote an inclusive and diverse work environment.

    Responsibilities

  • Develop and implement new machine learning models and algorithms for underwriting and customer management.Maintain existing models and conduct experiments to improve them. Test, validate and benchmarking is essential to ensure their accuracy and reliability.
  • Implementing monitoring systems to track model performance and quality over time. Regularly review and retrain models based on evolving data patterns and business requirements.
  • Apply advanced analytical methodologies and perform comprehensive analysis to address complex business challenges. Design and present evidence-based insights through charts and graphs, and communicate findings effectively to non-technical stakeholders.Clearly articulating the implications of data-driven decisions
  • Develop and scale analytic in-house python libraries for internal use cases.
  • Create clear and detailed documentation of the methodology and obtained results to ensure replicability and to facilitate understanding by other team members.
  • Collaborate with data engineers and ML engineer to develop automated orchestration of model pipelines.
  • Explore and test new data sources, algorithms and model features. Optimize and improve existing features.

    • Supplementary Duties

  • Share knowledge and results to peers and leaders.
  • Coach and mentor junior Data Scientists.
  • Presenting findings and insights to both technical and non-technical audiences.
  • Staying updated on the latest developments in data science, machine learning, and related fields. Exploring new tools, technologies, and methodologies to improve data science practices.

    • Minimum qualifications:

  • Degree in a quantitative discipline (e.g., Actuary, Mathematics, Physics, Statistics, Computer Science, or related field).
  • At least 3 years proven experience in Data Science and production programming experience in Python (Class oriented) and Pandas library.
  • Knowledge and experience with Machine Learning models, both supervised and unsupervised learning (e.g., classification, clustering, time series forecasting).
  • Statistics fundamentals: most common distributions, generalized linear models, hierarchical models (desirable), A/B testing, bootstrap, experiment design, simulation.
  • Strong SQL knowledge.
  • Independent worker. Your experience and capabilities should allow you to require little instruction and guidance.
  • Ability to communicate and translate technical solutions and methodologies to executive leadership.

    • Preferred qualifications:

  • Experience in the financial sector.
  • Experience working with Risk and Collections models.
  • Master's degree in a quantitative discipline (e.g., Statistics, Computer Science, Math, Engineering).
  • Effective problem solving and process improvement skills.
  • Ability to manage ambiguity, prioritizing needs, and delivering results in a dynamic environment.
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