Data Engineer2019 - 2019Greenchef (Toptal client)
Technologies: AWS DMS, PostgreSQL, Python, SQL, AWS Lambda, CircleCI, Git
- Built a DWH on AWS Redshift.
- Used AWS DMS to synchronize the production database (MongoDB) with AWS Redshift within seconds.
- Developed an AWS Lambda function to validate data quality.
- Built a CI/CD framework to develop and automatically run data analysis queries on AWS Redshift.
- Developed a set of microservices with AWS Lambda to automatically restart data pipelines in case of a failure.
Data Engineer2019 - 2019Xapo
Technologies: Python, SQL, Nifi, Redshift, Tableau, Google Data Studio, Excel
- Built a data warehouse on AWS (Airflow, Glue, Lambda, Redshift) to generate operational dashboards at every level in the business (customer support, compliance, debit card, etc.).
- Created ETL data pipelines with NiFi to sync data with databases in production.
- Created datamarts in BigQuery easily accessible using Excel, Tableau, or Google Data Studio.
- Collaborates with all areas of the organization to ensure data quality and integrity.
- Ensured compliance with the organization’s data governance policies.
Data Scientist (Remote)2017 - 2018Vodafone
Technologies: Hadoop, HDFS, Impala, Cloudera, PySpark, Python, Scala, Git, Tensorflow, Keras, Pandas, Numpy, Plotly
- Designed and developed large-scale machine learning algorithms with Impala, Spark, R (Shiny) and Python (Pandas/Numpy/Plotly/TF/Keras) to improve customer retention and product recommendation, analyze customer social network, and optimize marketing campaigns.
- Analyzed WhatsApp usage patterns with Spark to understand customer social network. This information would be used for marketing.
- Analyzed network performance and net promoter score to improve mobile network based on customer satisfaction.
Data Scientist2015 - 2017Jaguar Land Rover
Technologies: Hadoop, Spark, Scala, Python, R, Shiny, Tableau, HBase, Cassandra, Kafka, BigQuery, ElasticSearch, Logstash, Docker
- Managed stakeholders, planned projects, and designed a strategic roadmap for the Research DataLab team.
- Directly involved in deploying a scalable automotive data logging system on a fleet of 150 engineering vehicles, and developing large-scale data pipelines on AWS.
- Analyzed driving patterns to enhance advanced driver-assistance systems, anomaly detection to improve vehicle reliability and enable failure prediction, analysis of vehicle component usage to optimize reliability and cost.
- Created a data quality testing framework to ensure data integrity.
- Designed and developed a library that made it easy to run queries on vehicle data.
Data Scientist2015 - 2015Jaguar Land Rover
Technologies: AWS, Cassandra, HBase, Python, Java, Scala, Kafka, Docker
- Contributed to the design and development of an intelligent car and native cloud application on AWS to offer fully personalized driving experience.
- Designed performance metric to measure the quality of service for each component of the application.
- Developed machine learning models to predict user driving routines. Predictions were used for car preconditioning, fuel consumption estimation, destination prediction, or estimating time of arrival.
- Created a model to predict user destination based on calendar and email using natural language processing.
Machine Learning Engineer2012 - 2015Biomedical Engineering Group
Technologies: MATLAB, Hive
- Improved state-of-art motor imagery brain-computer interface performance by 10% using online adaptive ensemble classification.
Research Scientist2014 - 2014Brain Computer Interface Group, University of Essex, UK
Technologies: MATLAB, Python
- Worked on advanced brain signal processing with multitask learning, transfer learning, domain adaptation, deep learning, auto-encoders, and deep belief neural networks.
Software Engineer2010 - 2012Agroguia
Technologies: C++, Java, Digital Signal Processing, GPS
- Developed a machine learning application that allows steering a tractor by means of an EMG-based human-machine Interface.