Leonardo dos Santos Pinheiro, Statistics Developer in Sydney, New South Wales, Australia
Leonardo dos Santos Pinheiro

Statistics Developer in Sydney, New South Wales, Australia

Member since July 15, 2016
Leonardo is a data scientist and machine learning engineer with eight years of industry experience across the government, energy markets, finance, and consulting sectors. He is well versed in work with both small and big data, specializing in the development and deployment of AI systems, and in the application of machine learning and optimization algorithms to generate predictive analytics and improve business process.
Leonardo is now available for hire

Portfolio

  • BCG
    Python, OpenCV, TensorFlow, Metashape, AWS, Docker
  • Toptal
    Python, Deep Learning, Computer Vision, AWS, GCP, Docker, TensorFlow.
  • Servian
    Python, Scala, Spark, AWS, Hadoop, TensorFlow, Keras

Experience

Location

Sydney, New South Wales, Australia

Availability

Part-time

Preferred Environment

Linux, Jupyter, IntelliJ, VS Code

The most amazing...

...system I have developed is a web-based AI assistant that uses a sequence model for text classification to provide insights to analysts based on model bahavior.

Employment

  • Senior Data Scientist

    2019 - PRESENT
    BCG
    • Developed a PoC for stereo vision and DSM construction using satellite images.
    • Developed a Twitter analysis dashboard to measure tweet sentiments, network of influencers and visualize trends per tag/time.
    Technologies: Python, OpenCV, TensorFlow, Metashape, AWS, Docker
  • Data Scientist

    2018 - PRESENT
    Toptal
    • Built an object detection model for medical image analysis using TensorFlow.
    Technologies: Python, Deep Learning, Computer Vision, AWS, GCP, Docker, TensorFlow.
  • Senior Machine Learning Consultant

    2018 - 2019
    Servian
    • Developed and deployed a churn model for an insurance company.
    • Developed and deployed a convolutional network for customer spending forecasting using TensorFlow, Ansible, Docker, ECS, DynamoDB, and PostgreSQL.
    • Developed and deployed a text classification system using a convolutional model using TensorFlow and Spark.
    • Developed a data science strategy for a major financial institution. Mentored junior data scientists.
    • Explored a large corpus of insurance claims data using association rule mining, topic modeling, semantic similarity, and other text mining techniques.
    • Developed a machine comprehension PoC (based on Facebook's DrQA) using Pytorch, Flask, React and Google Cloud.
    Technologies: Python, Scala, Spark, AWS, Hadoop, TensorFlow, Keras
  • Data Scientist

    2017 - 2018
    Mojo Power
    • Developed and deployed a serverless linear model for load forecasting using Python, NumPy, and AWS Lambda.
    • Created a proof-of-concept Hidden Markov Model for load disaggregation.
    • Developed a model for credit scoring of energy customers.
    • Developed and deployed an LSTM model for load forecasting using PyTorch. Used topic modeling for exploratory data analysis of customer reviews.
    • Developed dashboards for analytics reporting on energy usage using Tableau.
    Technologies: Python, AWS Lambda, PostgreSQL, Tableau
  • Quantitative Developer

    2016 - 2017
    Macquarie Bank
    • Parsed and analyzed unstructured data of logs of order execution into SQL Server.
    • Back-tested optimal execution strategies.
    • Developed a Plotly dashboard to visualize market data.
    • Tested and investigated new trading strategies.
    • Tested machine learning algorithms for commodities trading.
    Technologies: Python, kdb+, SQL Server, Vagrant, Django, C#, Plotly
  • Quantitative Researcher

    2012 - 2016
    Securities Commision of Brazil
    • Developed regulatory research studies using statistical modeling (estimation and hypothesis testing).
    • Developed market risk reports and visualizations with time series analysis and forecasting using R.
    • Elaborated a risk monitoring system using Monte Carlo simulation and statistical estimation using Java.
    • Developed a data warehouse to aggregate data related to market risk and development of BI reports using BusinessObjects.
    • Led a data governance group to discover and catalog data sources across the whole organization.
    Technologies: R, SQL Server, SPSS, Python, Cognos, BusinessObjects, MS Office
  • Business Analyst

    2010 - 2012
    Brazilian Institute of Metrology
    • Processed modeling and analysis, using BPM.
    • Monitored business KPIs on Cognos dashboards.
    • Gathered requirements for internal systems developed by a development factory.
    Technologies: Cognos, Java, UML

Skills

  • Languages

    Python, SQL, R, Scala, Bash, Java, C#, Julia
  • Frameworks

    Spark, Hadoop, Windows PowerShell, Django, Flask
  • Libraries/APIs

    Scikit-learn, XGBoost, Pandas, NumPy, SpaCy, TensorFlow, SciPy, NLTK, OpenCV, PyTorch, Flask-RESTful, Node.js
  • Tools

    Jupyter, Tableau, Plotly, H2O AutoML, GitLab CI/CD, Git, AWS ECS, Apache Airflow, Cloudera, AWS CloudFormation, Talend ETL
  • Other

    Agile Data Science, Machine Learning, Natural Language Processing (NLP), Deep Learning, Computer Vision, A/B Testing, Visualization, Statistics, APIs, NLP, Recommendation Systems
  • Paradigms

    Scrum, Kanban
  • Platforms

    Docker, AWS Lambda
  • Storage

    AWS S3, AWS DynamoDB, InfluxDB, AWS RDS, MongoDB, Kdb+

Education

  • Master's degree in Applied Math
    2014 - 2016
    Getulio Vargas Foundation - Rio de Janeiro, Brazil
  • Bachelor's degree in Management Science
    2006 - 2009
    Getulio Vargas Foundation - Rio de Janeiro, Brazil
Certifications
  • AWS Certified Developer
    DECEMBER 2018 - DECEMBER 2020
    AWS

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