Data Science Specialist

Previous experience designing and building supervised ML models using Random Forests, Boosting, SVM or deep learning (some experience with at least one of the main libraries/frameworks like XGBoost, Sklearn and Tensorflow);

Understand the trade off and implementation differences between batch vs streaming;

Work with transactional DBs and analytical tools like Redshift, BigQuery and Athena;

Good knowledge of development tools like git, bash and containers.

Nice to have:

EBANX Education:

Financial support for undergraduate, graduate, and MBA programs to support your professional growth.

EBANX Skills:

Budget dedicated to workshops, courses, and certifications to encourage your continuous development.

Language Classes:

Spanish, English, and Portuguese lessons for your personal and professional development.

Your day-to-day impact:

Build and maintain machine learning models that are relevant to the payments industry (e.g. real-time transactional model, anomaly detection, routing optimization and churn prediction);

Work closely with devs and core business areas (fraud prevention, finance, commercial, products and marketing) to define business problems and create solutions leveraging our data;

Be able to propose new projects, gain stakeholder buy-in, calculate business value, be a cooperative team player and develop strong relationships with colleagues;

Explain and solve complex problems in straightforward terms;

Work directly with the data engineering team to create data pipelines and transformations necessary to be consumed by models;