Riccardo Volpato, Developer in Glasgow, United Kingdom
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Riccardo Volpato

Verified Expert  in Engineering

Project Scoping Developer

Glasgow, United Kingdom
Toptal Member Since
October 9, 2019

Riccardo is a senior software engineer with over seven years of experience developing web, back-end, and machine-learning systems. Having worked for Twitter and Satalia, an AI startup acquired by WPP, he is skilled in developing end-to-end products for a broad range of industries, including social media, data analytics, and government. As an experienced technical leader, Riccardo has headed engineering teams at Twitter and a government-tech startup he founded.


JavaScript, React, Google Cloud Platform (GCP), React Native, Back-end, GraphQL...
Google Cloud Platform (GCP), TensorFlow, Keras, Python, Time Series...
PigeonLine - Research-AI
SpaCy, Docker, SQL, PostgreSQL, Vue, JavaScript, Django, Python...




Preferred Environment

MacOS, Linux, Python, JavaScript, React, React Native, Django, Flask, TensorFlow

The most amazing...

...project I've developed was the complete rebuilt of Tweet-level analytics for Twitter.

Work Experience

Senior Software Engineer

2021 - 2022
  • Developed a new version of Tweeter Analytics, a screen that provides detailed feedback about the performance of a single tweet. Drove $9 million in quarterly revenue through promotions and converted 100% of users to professionals.
  • Developed a React library of charts, including a bar chart, pie chart, progress bar, etc., used by the entire web team to display any chart in the Twitter web application. We also included special accessibility features for visually impaired users.
  • Grew and led a team of eight engineers. Liaised with product, design, and research teams to establish and maintain a roadmap. Facilitated Agile ceremonies, kept team tempo, and mentored individual contributors.
  • Developed Professional Home, a new user-level overview of account activity for professional Twitter users. Took over the product from a stale team and launched it within two months.
Technologies: JavaScript, React, Google Cloud Platform (GCP), React Native, Back-end, GraphQL, Git, Data Visualization, Accessibility, Web Development, APIs, X (formerly Twitter)

Machine Learning Engineer

2017 - 2021
  • Produced a machine learning system for a large UK retailer to predict daily demand and recommend workforce allocation. This enabled the retailer to forecast hourly demand with 80% accuracy across 100+ locations.
  • Led various consultancy engagements in industries, such as finance and retail, to provide advice on how to develop systems to collect data and integrate artificial intelligence solutions in their business.
  • Developed an internal NLP system using Google Dialogflow to translate employees' questions into a natural language in database queries.
Technologies: Google Cloud Platform (GCP), TensorFlow, Keras, Python, Time Series, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Machine Learning, Facilitation, Project Scoping, Forecasting, Communication, Git, Artificial Intelligence (AI), Data Visualization

Chief Technology Officer

2016 - 2019
PigeonLine - Research-AI
  • Developed a product that helps government customers ingest employee data and recommends the most suitable employees for a new assignment. The product leveraged NLP to make semantic matches and was deployed on governments' on-premise servers.
  • Created a web application that allowed small municipalities to upload their own citizen satisfaction surveys, obtain an automated summary report, and compare their results with regional and industry benchmarks.
  • Collaborated with the New York University of Abu Dhabi and produced a tool to fetch, parse, and organize over 700GB of data as PDF attachments from the US Regulations.gov API to study citizen sentiment and predict public unrest.
  • Developed a web application that uses natural language processing to perform topic analysis on a text dataset. The application allows users to group excerpts by semantic relatedness and sentiment when given a large sample of documents.
  • Raised $1 million, alongside the CFO and CEO, to finance business expansion, technical development, and product growth.
  • Won the 2018 LSE Entrepreneur-of-the-Year Award and Distinguished Alumni of Dubai Future Accelerator.
Technologies: SpaCy, Docker, SQL, PostgreSQL, Vue, JavaScript, Django, Python, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Project Scoping, Communication, Entrepreneurship, Back-end, Git, Data Visualization, D3.js, Web Development, APIs, REST APIs

NLP Meets XAI: Top 5 Trends in Natural Language Processing Explainability

Researched and wrote an article focusing on recent explainability approaches in the domain of natural language processing. It argues that the future of computing is interpretable. The published article is popular among the machine learning community, with more than 500 reads per month.

The Chili Game | Social Web Game

A React and Next.js web game that was designed to help people get to know each other by answering questions of varying levels of intimacy, i.e., spiciness. The game was developed as a Next.js app and deployed using the Vercel ecosystem that includes detailed analytics about usage.

Deep Learning | Article

Explored neural language models' limits and advantages by creating one to re-create my own writing. I published a blog post illustrating the performance and limitations of my model, including detailed steps on how to reproduce the work.

Twitter Social Game

A web-based game that asks people to guess which of their friends wrote which tweet. I developed the game using Node.js, React, and the Twitter API and deployed it on my server. The game also displays a leaderboard with user scores that is connected to a Google Sheet with a Google Web API.

Reinforcement Learning Agent Learning Human Preferences

A research project that applies interpretability techniques to an artificial intelligence agent developed using reinforcement learning (RL). My team and I worked on training custom RL agents using TensorFlow and PyTorch. Also, we later inspected whether such agents had learned about their environment and simulated humans that acted within them.

Time Series Python Library

A time series library to perform data analysis and train machine learning models on time series data. It was developed as part of the Kaggle ASHRAE Great Energy Challenge. I created the library using Python, scikit-learn, LightGBM, NumPy, and pandas.

Accessibility of Twitter Charts

Led the development of making the charts in the Twitter web library accessible to visually impaired users. By leveraging the Web Audio API, we enabled users to listen to charts by translating numbers to pitched sounds and written chart descriptions.
2016 - 2017

Master of Science Degree in Decision Science

London School of Economics and Political Science - London, United Kingdom

2012 - 2015

Bachelor's Degree in Economics and Statistics

Bocconi University - Milan, Italy


Deep Learning | 5-course Specialization

DeepLearning.AI | via Coursera


Chinese HSK 5

Confucius Institute


X (formerly Twitter) API, REST APIs, SpaCy, Keras, TensorFlow, React, Node.js, D3.js, Vue, PyTorch




Python, JavaScript, SQL, GraphQL


Data Science, Management


X (formerly Twitter), Google Cloud Platform (GCP), Docker




Django, Flask, React Native, Next.js


Communication, Project Scoping, Facilitation, Machine Learning, Web Analytics, Back-end, Data Visualization, Accessibility, Web Development, APIs, Natural Language Processing (NLP), Time Series, Forecasting, Deep Learning, Entrepreneurship, Artificial Intelligence (AI), Generative Pre-trained Transformers (GPT), Consulting, Explainable Artificial Intelligence (XAI), Deep Reinforcement Learning, Psychology, Behavioral Science, Workshop Facilitation

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