(Mex) Big Data Engineer Work with Machine Learning

hace 3 días

Ciudad de México Prometeo Soluciones A tiempo completo

**Descripción del puesto**:UMBA is looking for a **Big Data Engineer** with an **Engineering background** that will help us **manage and gather information** from different data points, **create data lakes and data pipelines.** Our most complex system is our risk model, your day-to-day will include feature generation and model training using **machine learning techniques**, developing **A/B testing procedures**, implementing **automated model retraining**, and **creating new projects based on your data.**You will be working with a small, but highly technical team. We have 250,000 users and work to ensure continuous uptime and constant improvement. We train and deploy new machine learning models regularly and subscribe to data-driven decision making, **you will not be just an implementer, but a valued opinion at the table.****Requisitos**:- **4-5 years of experience** with **Machine Learning pipelines** in production.- **Advanced English skills**, both written and spoken.- Experience with **Machine Learning pipelines** on production environments (model deployments).- Experience **building** and **optimizing 'big data' data pipelines, architectures, and data sets.**:- Knowledge of **AWS** (S3, EMR, EC2, Sagemaker, Lambda, Glue, Athena).- Experience with **big data tools**: Hadoop, Spark, Kafka, etc.- Experience with **NoSQL databases** (MongoDB, Neo4J, Neptune)- Experience **developing APIs**:- **Strong SQL skills****Beneficios**:- Medical and life insurance- Stock options**Detalles**:Área: Tecnología, Sistemas y Telecomunicaciones/Análisis de DatosModo de trabajo: Presencial**Contrata**:Our mission at **UMBA **is to use **machine learning** to allow us to create intelligent, affordable financial products for emerging markets. Umba launched into the Kenyan market in November 2018 and offers a number of **digital banking products** to its users through an **Android App.**This platform uses **machine learning** and **big data** to build credit scores to optimize risk exposures and allows users to apply, receive, and repay micro-loans and through their smartphones. Once a user creates an account we validate their information and make lending decisions based on the information they give us and hundreds of data points we take from their smartphone with their permission.Our machine learning models are in a state of **constant improvement** and **we use AI and automation **to deliver the lowest cost banking solutions for our growing customer base. We have built out a large data collection platform, with our data warehouse storing over 100m rows of data for accurate credit scoring.**Video destacado**:

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