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

Leonardo dos Santos Pinheiro

Statistics Developer

Sydney, New South Wales, Australia
Toptal 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.

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


Data Science - 10 yearsStatistics - 7 yearsSQL - 6 yearsR - 6 yearsPython - 5 yearsGenerative Pre-trained Transformers (GPT) - 4 yearsNatural Language Processing (NLP) - 4 yearsGPT - 4 years


Sydney, New South Wales, Australia



Preferred Environment

Visual Studio Code (VS Code), Jupyter, Linux, PyCharm, Windows Subsystem for Linux (WSL), Google Cloud Platform (GCP)

The most amazing...

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

Work Experience

2019 - PRESENT

Senior Data Scientist

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, TensorFlow, OpenCV, Python
2018 - PRESENT

Data Scientist

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), Computer Vision, Deep Learning, Python
2018 - 2019

Senior Machine Learning Consultant

  • 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, Spark, Scala, Python
2017 - 2018

Data Scientist

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
2016 - 2017

Quantitative Developer

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
2012 - 2016

Quantitative Researcher

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
2010 - 2012

Business Analyst

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



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


Spark, Hadoop, Windows PowerShell, Django, Flask


Keras, Scikit-learn, XGBoost, Pandas, NumPy, SpaCy, OpenCV, TensorFlow, SciPy, Natural Language Toolkit (NLTK), Luigi, PyTorch, Flask-RESTful, Node.js


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


Data Science, Scrum, Kanban


Artificial Intelligence (AI), Dashboards, Agile Data Science, Machine Learning, Natural Language Processing (NLP), Computer Vision, Deep Learning, GPT, Generative Pre-trained Transformers (GPT), A/B Testing, Visualization, Statistics, APIs, Scraping, Analytics, Dashboard Design, SAP BusinessObjects (BO), Microsoft 365, Recommendation Systems, Windows Subsystem for Linux (WSL)


Docker, AWS Lambda, Linux, Google Cloud Platform (GCP), Amazon Web Services (AWS), Apache Kafka, Visual Studio Code (VS Code)


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


2014 - 2016

Master's Degree in Applied Math

Getulio Vargas Foundation - Rio de Janeiro, Brazil

2006 - 2009

Bachelor's Degree in Management Science

Getulio Vargas Foundation - Rio de Janeiro, Brazil



AWS Certified Developer