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 4, 2019
Leonardo is a machine learning engineer with 10 years of industry experience across the government, energy markets, finance, healthcare, and consulting. He is well versed in work with analytics, data engineering, and machine learning, specializing in the development and deployment of AI systems for computer vision, NLP, and recommender systems.
Leonardo is now available for hire


  • BCG Digital Ventures
    Amazon Web Services (AWS), Docker, AWS, TensorFlow, OpenCV, Python
  • Toptal Project
    Amazon Web Services (AWS), TensorFlow, Docker, Google Cloud Platform (GCP)...
  • Servian
    Amazon Web Services (AWS), Keras, TensorFlow, Hadoop, AWS, Spark, Scala, Python



Sydney, New South Wales, Australia



Preferred Environment

VS Code, Jupyter, Linux, PyCharm, WSL, Google Cloud Platform (GCP)

The most amazing...

...project I've developed is a computer vision system to identify crop diseases and recommend treatments.


  • Senior Data Scientist

    2019 - PRESENT
    BCG Digital Ventures
    • Used stereo vision and image segmentation on satellite imagery to aid an infrastructure company in vegetation management. The system was used to map the risk of vegetation encroachment with assets.
    • Developed a Twitter analysis dashboard to measure tweet sentiments, a network of influencers, and visualize trends per tag/time to aid strategic designers in research.
    • Developed a gradient boosting model for activity classification using sensor data for a supply chain startup. The system was used to track illegal activity at different points in the supply chain.
    • Built image classification models for crop recognition and crop pest/disease recognition for a farming startup. The system supported advisory for smallholder farmers in southeast Asia.
    • Built a recommender system for a cashback program startup, enabling personalization of content to drive engagement in the platform.
    • Created a performance dashboard for a farming startup using Data Studio and BigQuery.
    Technologies: Amazon Web Services (AWS), Docker, AWS, TensorFlow, OpenCV, Python
  • Data Scientist

    2018 - PRESENT
    Toptal Project
    • Built an object detection model for medical image analysis using TensorFlow.
    • Created a data science strategy for a lending start-up.
    • Created a trading Forex back-testing platform using Python and AWS.
    • Created Forex trading algorithms using Bayesian machine learning and deep learning with technical indicators as features. Used Python, TensorFlow, and TensorFlow-probability.
    Technologies: Amazon Web Services (AWS), TensorFlow, Docker, Google Cloud Platform (GCP), AWS, Computer Vision, Deep Learning, Python
  • Senior Machine Learning Consultant

    2018 - 2019
    • Developed and deployed a churn model using gradient boosting 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.
    • Designed 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.
    • Created a open domain chatbot based on machine comprehension (Facebook's DrQA) using PyTorch, Flask, React, and DialogFlow.
    • Assisted in the development of a person tracking system using Yolo v2 and Kalman filters for a major Australian retail company.
    • Assisted with a markdown system based on demand forecasting using Facebook's Prophet and revenue optimization using mixed-integer linear programming.
    Technologies: Amazon Web Services (AWS), Keras, TensorFlow, Hadoop, AWS, Spark, Scala, Python
  • 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.
    • Developed dashboards for analytics reporting on energy usage using Tableau.
    • Used topic modeling for exploratory data analysis of customer reviews.
    • Worked on a PoC for solar panel detection on satellite images using Facebook's Detectron.
    Technologies: Tableau, PostgreSQL, AWS Lambda, Python
  • 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: Plotly, C#, Django, Vagrant, Microsoft SQL Server, Kdb+, Python
  • Quantitative Researcher

    2012 - 2016
    Comissão de Valores Mobiliários
    • Developed regulatory research studies using statistical modeling (estimation and hypothesis testing).
    • Created 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: Microsoft 365, SAP BusinessObjects (BO), IBM Cognos, Cognos 10, Python, SPSS, Microsoft SQL Server, R
  • 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: UML, Java, IBM Cognos, Cognos 10


  • Languages

    Python, SQL, R, Scala, Bash, Julia, JavaScript
  • Frameworks

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

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

    Jupyter, Tableau, Plotly, H2O AutoML, GitLab CI/CD, Git, Amazon ECS (Amazon Elastic Container Service), Apache Airflow, IntelliJ, VS Code, SPSS, Vagrant, AWS CloudFormation, Talend ETL, PyCharm
  • Paradigms

    Data Science, Scrum, Kanban
  • Other

    Artificial Intelligence (AI), Dashboards, Agile Data Science, Machine Learning, Natural Language Processing (NLP), Computer Vision, Deep Learning, A/B Testing, Visualization, Statistics, APIs, Scraping, Analytics, Dashboard Design, SAP BusinessObjects (BO), Microsoft 365, AWS, Recommendation Systems, WSL
  • Platforms

    Docker, AWS Lambda, Linux, Google Cloud Platform (GCP), Amazon Web Services (AWS), Apache Kafka
  • Storage

    Amazon S3 (AWS S3), Amazon DynamoDB, InfluxDB, PostgreSQL, Microsoft SQL Server, MongoDB, Kdb+, Neo4j


  • 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


  • AWS Certified Developer
    DECEMBER 2018 - DECEMBER 2020

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