Data Scientist
2017 - PRESENTSatalia- Built a convolutional neural network that predicts spatio-temporal grocery deliveries demand. This improved the performance of a last-mile delivery optimization algorithm and enabled businesses to dynamically price deliveries based on the forecasted cost.
- Conducted various consultancy workshops to assess technological needs and facilitate the adoption of artificial intelligence solutions in industries such as finance and retail.
- Researched and developed a proof-of-concept algorithm to determine the best solver algorithm for a given optimization problem to be embedded as a machine learning layer of on-demand optimization software. My research focused on computer science problems known as Automatic Algorithm Selection and Configuration.
- Produced three machine learning models for a large UK retailer: Recurrent neural network to predict daily demand, dense network to predict the hourly distribution of daily demand, and an optimization model to recommend hourly workforce allocation. This enabled the retailer to forecast hourly demand with 80% accuracy.
Technologies: Python, Keras, TensorFlow, Google Cloud Platform, OptimizationFounding CTO
2016 - 2019PigeonLine- Constructed the company’s technical foundations, which involved architecting and deploying machine learning algorithms, back-end APIs, front-end interfaces, and the server infrastructure. To achieve this, I jointly managed a team of four developers.
- Developed an interactive topic analysis web application using neural word embeddings.
- Designed and delivered an introductory course on AI and Social Sciences for the London School of Economics. It used our interactive topic analysis tool to teach students how Natural Language Processing can aid Social Science research.
- Produced in collaboration with the New York University of Abu Dhabi, a tool to fetch, parse and organize over 700GB of data (including PDF attachments) from the US regulations API to study citizen sentiment and predict public unrest.
- Raised $1 million, alongside the CFO and CEO to finance business expansion, technical development, and product growth.
- Researched, developed, and deployed an NLP matching algorithm that automatically sourced the most suitable civil servants for new government projects for a Prime Minister’s office in the Gulf Region.
- Won the 2018 LSE Entrepreneur-of-the-Year Award and Distinguished Alumni of Dubai Future Accelerator.
Technologies: Python, Django, JavaScript, Vue.js, PostgreSQL, SQL, Docker, Spacy
Riccardo Volpato
Natural Language Processing (NLP) Developer in London, United Kingdom
Member since September 14, 2019
Riccardo has developed numerous machine learning solutions for large-scale enterprises and governments across the world. He has extensive expertise with time series data and forecasting, having developed a demand forecasting system for a UK retailer with over 100 stores. Riccardo also has advanced skills in Natural Language Processing; for example, he developed a system to match work descriptions and candidate profiles for a national government.
Riccardo is now available for hire
Portfolio
- SataliaPython, Keras, TensorFlow, Google Cloud Platform, Optimization
- PigeonLinePython, Django, JavaScript, Vue.js, PostgreSQL, SQL, Docker, Spacy
Experience
- Python 4 years
- Data Science 4 years
- Natural Language Processing (NLP) 3 years
- Keras 2 years
- Time Series 2 years
- Django 2 years
- Swift 1 year
- Fast.ai 1 year
Availability
Part-time
Preferred Environment
Linux, Unix, macOS
The most amazing...
...project I've developed was a data science infrastructure (front end, back end, machine learning algorithms, and deployment) for a government analytics startup.
Employment
Experience
- Automating Writing (Development)https://volpato.io/blog/2019/can-i-automate-myself-a-brief-on-language-models/
I explored neural language models' limits and advantages by building one to re-create my own writing.
- NLP meets XAI: Top 5 Trends in NLP Explainability (Development)https://volpato.io/blog/2019/nlp-meets-xai/
Researched and wrote an article that focuses on recent explainability approaches in the domain of Natural Language Processing (NLP). The future of computing is interpretable.
- LSE Entrepreneur of the Year 2018 (Other amazing things)https://www.facebook.com/lseps/posts/lse-entrepreneur-of-the-year-and-social-entrepreneur-of-the-year-announced-last-/10156078031958347/
In 2018, I led the startup I cofounded trough the yearly LSE Generate Competition. After three stages, during which we presented our innovations, technology, achievements and business strategy, in front of panels of judges we were recognised as LSE Entrepreneur of the Year 2018.
Skills
Languages
Python, JavaScript, SwiftParadigms
Data ScienceOther
Communication, Project Scoping, Facilitation, Machine Learning, Natural Language Processing (NLP), Time Series, ForecastingFrameworks
Django, FlaskLibraries/APIs
Keras, Fast.ai, TensorFlowStorage
PostgreSQL
Education
- Master of Science degree in Decision Science and Operational Research2016 - 2017London School of Economics - London, UK
- Bachelor's degree in Economics and Statistics2012 - 2015Bocconi University - Milan, Italy
Certifications
- Deep Learning, 5-course SpecializationJUNE 2019 - PRESENTCoursera
- HSK 5 (Chinese Language)MAY 2015 - PRESENTConfucius Institute
