Senior/Lead Data Scientist - Xico, México - Agileengine

    Agileengine
    Default job background
    Descripción
    ID: 14204
    What you will do
    • Ingesting, structuring and analyzing a wide range of unstructured data sources;
    • Designing, maintaining and orchestrating data pipelines in an AWS environment for production processing and training flows;
    • Continuously evaluate, analyze, test and improve the quality, privacy and performance of our data systems;
    • Contribute across the product, where from front end UX and product design, API/systems architecture and ML processing/training.

    Must haves- 3+ years of experience ingesting, analyzing and structuring a wide variety of data sources;
    • Significant experience building and maintaining data pipelines in a production environment;
    • Strong database/SQL, python, pandas (or equivalent) experience;
    • Prior experience working in fast paced environments and tackling problems across the stack with quick iterations while maintaining a high quality bar;
    • Upper intermediate English level.

    Nice to haves
    • Significant healthcare data experience;
    • Extensive production AWS, container and/or data orchestration experience;
    • MLE Experience pytorch, scikit learn, etc.
    ;
    • Fullstack development experience (JS/TS/Node in particular);
    • Demonstrated experience in similar roles in a startup or consultancy.

    The benefits of joining us-
    Professional growthAccelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps-
    Competitive compensationWe match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities-
    A selection of exciting projectsJoin projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands-
    FlextimeTailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office - whatever makes you the happiest and most productive.


    Work Location:
    In person