Julio Oliveira, Machine Learning Developer in Philadelphia, PA, United States
Julio Oliveira

Machine Learning Developer in Philadelphia, PA, United States

Member since August 25, 2020
Julio is a machine learning engineer, specializing in big data analytics. For the past three years, he has helped major companies, such as Fiat Chrysler Automobiles and a Brazilian credit bureau, improve their machine learning platforms. By combining big data and analytics, he has developed machine learning pipelines that run hundreds of machine learning models. In addition to his industry experience, Julio teaches university and other online courses in machine learning and data science.
Julio is now available for hire

Portfolio

  • Alura
    Python, Flask, Machine Learning, Data Science, Kubernetes, Docker...
  • Live University
    Python, Data Science, Machine Learning, SQL, Google BigQuery
  • Boa Vista SCPC
    Python, PySpark, Hadoop, Cassandra, Apache Hive, Impala, Apache Kafka...

Experience

Location

Philadelphia, PA, United States

Availability

Part-time

Preferred Environment

Python, PySpark, Kubernetes, Google Cloud Platform (GCP), Apache Beam, Apache Airflow, Cassandra, Hadoop, Apache Kafka, Apache Hive

The most amazing...

...project I've developed is a machine learning platform for a Brazilian credit bureau, on top of GCP with a centralized feature store.

Employment

  • Instructor

    2019 - PRESENT
    Alura
    • Taught and developed courses in machine learning for digital marketing.
    • Taught and developed courses in MLOps for machine learning and APIs.
    • Taught and developed courses in image recognition with Twitter and Computer Vision API.
    Technologies: Python, Flask, Machine Learning, Data Science, Kubernetes, Docker, Google Cloud Platform (GCP), Machine Learning Operations (MLOps), SQL, Google BigQuery
  • Assistant Professor

    2018 - PRESENT
    Live University
    • Taught and developed courses in Python for machine learning.
    • Taught and developed courses in Python for anomaly detection.
    • Taught and developed courses in machine learning with Twitter and Facebook APIs.
    Technologies: Python, Data Science, Machine Learning, SQL, Google BigQuery
  • Machine Learning Engineer

    2018 - 2020
    Boa Vista SCPC
    • Designed and developed a centralized feature store platform for data science, capable of running thousands of machine learning features on a daily basis.
    • Designed and developed a model deployment platform with GCP, which receives ten new machine learning models per month.
    • Significantly improved the data science team's platform, software, and tools, resulting in 100% cloud-native technologies for machine learning.
    • Migrated 100% of the analytics platform from on-premises to GCP.
    Technologies: Python, PySpark, Hadoop, Cassandra, Apache Hive, Impala, Apache Kafka, Google Cloud Platform (GCP), Google Kubernetes Engine (GKE), Apache Airflow, Machine Learning, Data Science, Credit Risk, Kubernetes, Google Cloud Functions, Machine Learning Operations (MLOps), SQL, Google BigQuery, Google Bigtable, Big Data Architecture, ETL, Data Engineering, AWS
  • Data Scientist

    2017 - 2018
    MuchMore
    • Developed and implemented a data lake for centralizing all digital marketing data.
    • Built an anomaly detection model to predict unusual behavior in product performance, resulting in millions of dollars in savings.
    • Improved digital marketing sales by 200% by constantly creating new strategies and goals.
    Technologies: Python, Google Cloud Platform (GCP), Google Analytics, Google Analytics 360, Google Ads, Facebook, Flask, Anomaly Detection, Digital Marketing, Big Data, SQL, Google BigQuery, Big Data Architecture, ETL, Data Engineering
  • Warehouse Supervisor

    2015 - 2016
    Laticínios Vida
    • Implemented a business intelligence system for monthly sales reporting.
    • Designed and analyzed a fractional factorial design experiment, which improved. a product bill of materials (BOM).
    • Implemented a mobile app for customer orders, reducing the lead time on the invoicing process by 60%.
    Technologies: Python, Excel VBA, Supply Chain, Business Intelligence (BI), SQL
  • Supply Chain Intern

    2015 - 2015
    Mullinix Packages
    • Reduced lead time in the SKU tracking process by 70%.
    • Served as the Six Sigma team leader on the project to improve inventory accuracy.
    • Served as the Six Sigma team leader on the overpull reduction project.
    Technologies: Excel VBA, Excel 2013, Six Sigma
  • Computer Technician

    2012 - 2014
    Projeta Mídia Digital
    • Doubled the company's overall sales in the first year.
    • Researched, designed, and implemented two products: Digital Signage and Totem/Kiosk.
    • Eliminated waste by improving processes and developing standard practices.
    Technologies: Computer Repair, Hardware Repair, Sales
  • Computer Technician Intern

    2010 - 2010
    Laticínios Vida
    • Created three control systems in Excel, which are still used today: hours worked, delivery control, and freight payment.
    • Reduced the company's transport costs for small vehicles.
    • Improved the delivery system by eliminating wasteful time and movement.
    Technologies: Excel VBA, Excel 2013, Supply Chain

Experience

  • Image Recognition with Twitter and Computer Vision API
    https://github.com/jcalvesoliveira/twitter-api

    A Python project, retrieving data from the Twitter API and classifying images posted on Twitter by famous people, using the Azure Computer Vision API. I developed the entire project for one of my machine learning classes.

  • Selecting Soccer Players in the Cartola FC Fantasy Soccer Game
    https://github.com/henriquepgomide/caRtola/blob/master/src/python/markov-chain-lpp.ipynb

    A project for selecting the best 11 players for a round in the Brazilian fantasy soccer game. I created it using a Markov model with linear optimization, but it was restricted by the financial resources available.

  • Statistics Processing with Python and gRPC
    https://github.com/jcalvesoliveira/statistics-processing

    A gRPC microservice developed in Python to calculate summary statistics over a transactions dataset. The service includes a GitHub Actions pipeline, deployment to Kubernetes, and monitoring with Prometheus and Grafana.

Skills

  • Languages

    Python, SQL, R
  • Paradigms

    Data Science, ETL, Anomaly Detection, Business Intelligence (BI), Six Sigma, Linear Programming, Microservices
  • Platforms

    Google Cloud Platform (GCP), Docker, Kubernetes, Apache Kafka, Google Analytics 360, Azure, Amazon Web Services (AWS), Databricks, AWS Lambda
  • Other

    Artificial Intelligence (AI), Machine Learning, Big Data, Analytics, Credit Risk, Machine Learning Operations (MLOps), Google BigQuery, Data Engineering, Big Data Architecture, Google Cloud Functions, Digital Marketing, Supply Chain, Lean, Google Ads, Facebook, Markov Model, Linear Optimization, Computer Vision, Streaming, APIs, Prometheus, AWS
  • Frameworks

    Flask, Spark, Hadoop, gRPC
  • Libraries/APIs

    PySpark
  • Tools

    Apache Beam, Apache Airflow, Impala, Google Kubernetes Engine (GKE), Google Analytics, Grafana
  • Storage

    Google Bigtable, Cassandra, Apache Hive

Education

  • MicroMasters Program Certificate in Artificial Intelligence
    2019 - 2020
    Columbia University - Online
  • Specialization (Masters Level) in Big Data Analytics
    2017 - 2018
    The Institute of Management Foundation (FIA) - São Paulo, SP, Brazil
  • Bachelor's Degree in Industrial Engineering
    2011 - 2017
    Montes Claros Technology and Science University - Montes Claros, MG, Brazil
  • Exchange Program in Industrial Engineering
    2014 - 2015
    Indiana Tech - Fort Wayne, IN, USA
  • Associate's Degree in Computers
    2008 - 2010
    Montes Claros Technical School - Montes Claros, MG, Brazil

Certifications

  • Microsoft Professional Program for Data Science
    NOVEMBER 2017 - PRESENT
    Microsoft
  • Green Belt Six Sigma Certification
    MAY 2015 - PRESENT
    American Society for Quality (ASQ)

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