- 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.
- Ad-hoc exploratory analysis and experiments.
- Promote the use of data as the main driver for decision making.
- Should be proficient at writing complex codes with languages like: Python, Pyspark and SQL.
- Relevant work experience working with core compute and storage cloud services (preferably AWS).
- 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.
- Experience in design solutions based on AWS services and tools (Lambda, Kinesis Data Stream, Kinesis Data Firehose, S3, Dynamo, OpenSearch, EMR, Sagemaker, ElastiCache), carefully read the docs, implement the entire architecture you designed with the support of your peers, and document it.
- Some experience with visualization tools (e.g. Tableau, Qlik or Looker).
- Previous experience working in a startup environment.
- Spanish, English, and Portuguese classes;
- Meal Allowance;
- Transportation voucher (if needed);
- WAVES - Program of goals and results (variable compensation);
- EBANX Play - Wellness (Gympass, e-Sports, SESC );
- EBANX Education: financial support for undergraduate, graduate, and MBA programs so you can develop important skills for your career;
- EBANX Skills: budget for workshops and courses;
- EBANX Flexible: Birthday Day Off;
- Semi-flexible hours (8 hours a day - Monday to Friday);
- EBANX Family: Daycare assistance, extended leave for caregivers and support program for children and pregnant women;
- EBANX Health: Health and Dental Insurance, with subsidy for dependents and medicine subsidy for ebankers;
- Life Insurance: Life Insurance 100% paid by EBANX;
- Blue Club: Exclusive discount for ebankers in bakeries, restaurants, courses, electronics stores, and more
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Machine Learning Engineering Specialist - São Paulo, Brasil - EBANX
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Descrição
EBANX is the leading payment platform connecting global companies with customers from the fastest-growing digital markets in the world.
Since the beginning of our journey, we have had one mission: to provide global access for everyone. We believe that transforming challenges into opportunities and making the impossible part of the journey is crucial That's precisely why we created a payment technology that builds bridges between people and businesses every day in 29 rising markets across the globe.
We call ourselves ebankers, we are global thinkers, we value diversity, we foster creativity and we work hard to connect businesses and people worldwide through payments. Let's make history together?
As a Data Scientist Specialist focused on MLOPs your mission will be to build and deploy machine learning models to serve multiple business units of the company.
You will also be responsible for:
Main requirements for this position:
What else would we like to see?
EBANX offers: