Pietro Grandinetti
Verified Expert in Engineering
Data Science Developer
Milan, Metropolitan City of Milan, Italy
Toptal member since November 20, 2017
Pietro is a systems engineer with a professional background as a software developer and a PhD in large-scale optimization, from the Technology Institute of Grenoble. Equally at ease in applied science and software positions, he enjoys designing and prototyping systems in Python, R, and C using web and data science tools. He likes new challenges and loves lifelong learning.
Portfolio
Experience
Availability
Preferred Environment
Linux, C, Python, Amazon Web Services (AWS), Go, PostgreSQL
The most amazing...
...thing I've built was a distributed, efficient, mixed integer optimization algorithm to design the optimal schedule of traffic lights in large cities.
Work Experience
Chief Technology Officer
Pentadata
- Built back-end systems that comprised several microservices, including APIs, Cron, AWS RDS, AWS Lambda, Elasticsearch, and Docker Swarm. Used Terraform to develop and maintain reproducible infrastructures.
- Managed a team of software developers and contractors.
- Passed a SOC 2, Type 2 official security audit, with final reporting about the company process and procedures, technological security, business continuity, and data protection and privacy. No control exceptions were noted from the auditors' side.
- Integrated multiple financial data sources into a new and unique API system with data cleaning and aggregation.
- Passed the penetration test on the AWS infrastructure, including servers, database, and file storage, with no security risks found.
- Developed machine learning algorithms and deployed them into the production environment, serving more than a million daily requests.
- Created GRPC services in Go to implement authentication, storage lookup, and RPC integration with other programming languages.
System Architect | Developer
Toptal Client
- Built the MVP of an API platform in Python/Flask and deployed scalable architecture in AWS and RDS.
- Designed a machine learning API built off scikit-learn and deployed in Flask.
- Designed highly scalable architecture in AWS and passed penetration testing and security audits.
Software Developer
Motorola Solutions
- Served as a core member of the Python development team.
- Constructed a data engineering pipeline, which included Python, SQL, and Oracle Cloud Commerce.
- Built a batch processing infrastructure for periodic big data engineering.
- Interfaced Python code with different SQL database systems.
- Created REST APIs and triggers for cron jobs, deployed in the AWS Linux server.
Research Scientist
UCLA
- Participated in the Long Program: Science at Extreme Scales—Where Big Data Meets Large-scale Computing.
- Contributed to state-of-the-art research on big data and machine learning.
- Defined new directions of industrial and academic research directions in the field.
Python Developer
Gridcell (via Toptal)
- Developed a RESTful API in a Django REST Framework.
- Created a WebSocket connection with Django channels.
- Built the client- and server-side for data streaming through AWS IoT and AWS Kinesis.
- Developed and queried Elasticsearch indexes via a Python client.
Data Scientist
RankSense
- Implemented convex and non-convex optimization algorithms for the reranking of web pages.
- Implemented forecast and prediction of page sales time series.
- Developed an exploratory analysis of Google Analytics Data.
- Created large-scale optimal procedures in native scientific Python, with NumPy, and Pandas.
- Developed deep learning and artificial intelligence (AI) systems for automated search engine optimization (SEO).
Software Developer
LegalKite
- Built a REST API for LegalKite.com with a Django-REST framework.
- Scraped Swiss law code and stored the data using PostgreSQL which allowed the creation of personal annotations.
- Supported search optimization with Elasticsearch through a database of laws and annotations.
- Deployed the system entirely into AWS facilities (RDS, Elasticsearch service, and EC2).
- Wrote deep learning and latent semantic indexing (LSI) algorithms for text classification.
Software Developer
Bluesophy
- Created a chatbot that acts as recommendation system.
- Incorporated smart search methods in the existing database with a Django ORM.
- Installed a syntactic analysis of input sentences, using NLTK.
- Integrated the bot within a standard web architecture (Angular and Django).
- Generated human-friendly answers with a hyperlink redirection to favorite items.
Research Engineer
CNRS
- Created a microscopic simulator of a road traffic network in Grenoble (FR), using the Aimsun simulator.
- Designed a centralized and distributed control algorithms for intelligent traffic lights.
- Integrated numerical optimization procedures into the Aimsun architecture.
- Created simulative comparisons with an industrial-strength controller.
- Developed a big-data analysis of microscopically generated road traffic data.
Experience
Portability | The Future Of Financial Data
https://www.forbes.com/sites/forbestechcouncil/2021/12/01/portability-the-future-of-financial-dataPut Data Ownership Where It Belongs: With The Consumer
https://www.forbes.com/sites/forbestechcouncil/2021/07/06/put-data-ownership-where-it-belongs-with-the-consumer/Road Network Macrosimulator
https://github.com/pgrandinetti/traffic-macrosimulatorKatie DJ
https://github.com/pgrandinetti/katiedjPlume | Compiler Learning Language Tool
https://github.com/pgrandinetti/compilersI spoke about the theory and practice of compilers and how I built Plume in a series of articles published at the link below.
LegalKite
Education
PhD Degree in Optimization of Large Scale Networks
Grenoble Institute of Technology - Grenoble, France
Master's Degree in Automation Engineering
University of Calabria - Rende, Italy
Bachelor's Degree in Computer Engineering
University of Calabria - Rende, Italy
Certifications
TensorFlow: Advanced Techniques Specialization
Coursera
TensorFlow in Practice
Deeplearning.ai (via Coursera)
Data Science
Johns Hopkins University (via Coursera)
Deep Learning
Deeplearning.ai (via Coursera)
Machine Learning
Stanford University (via Coursera)
Skills
Libraries/APIs
TensorFlow, Pandas, React.js
Tools
MATLAB, Docker Swarm, Terraform
Languages
R, Python, SQL, Java, C, Haskell, Go
Frameworks
Flask, Django, Django
Paradigms
REST, SEO
Platforms
AWS, Docker, AWS Lambda, Linux
Storage
PostgreSQL, Elasticsearch, Oracle RDBMS, AWS
Other
Freelance Design, APIs, Data Science, Optimization, AWS RDS, FastAPI, Deep Learning, Machine Learning, Site Reliability, NLP, Aimsun, Big Data Architecture, Large-scale Computing, Data Privacy, Writing & Editing, Simulations, WebSockets, Generative Pre-trained Transformers (GPT)
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