Giuseppe Vettigli - Senior Data Science Manager

Giuseppe Vettigli

Senior Data Science Manager

Cambridge, England, United Kingdom

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Summary

🤩

Rockstar

🎓

Top School

Giuseppe Vettigli is a Senior Data Science Manager based in Cambridge with 12 years of experience applying ML and AI to deliver measurable business value across energy and utilities. He leads teams that design and deploy transparent, scalable models—ranging from churn and pricing engines to LLM-driven root-cause analysis—while partnering with C-level stakeholders to turn analytics into strategy. An active researcher and educator, he authored MiniSom (the most-used Python SOM implementation), has contributed to scikit-learn, and holds NLP/AI publications with 300+ citations. His background spans startups, research labs and enterprise production (AWS, Azure, Databricks), giving him both academic depth and production-grade engineering rigor. Known for clear visual communication (“I love charts!”), he blends hands-on coding with mentorship to build maintainable, auditable solutions. He also brings a rare combination of product-focused full-stack contributions (visualisations and UI work on MiniSom examples and energy challenge entries) that make complex models accessible to stakeholders.

12 years of coding experience

13 years of employment as a software developer

Master of Science (MSc) 2 years degree Computer Science, Master of Science (MSc) 2 years degree Computer Science at University of Naples ‘Parthenope’

Italian, English

Github Skills (13)

html10

data-visualizations10

algorithm10

algorithms10

machine-learning10

data-visualization10

data-visualisation10

python10

implement10

numpy10

javascript8

scikit8

scikit-learn8

Programming languages (4)

CTeXHTMLPython

Github contributions (5)

JustGlowing/minisom

Jul 2013 - Jan 2023

:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

Role in this project:

Back-end Developer & UI Designer

Contributions:19 releases, 23 reviews, 437 commits in 9 years 8 months

Contributions summary:Giuseppe made significant contributions to the project by adding and improving the Iris dataset visualization example, which demonstrates the application of the Self Organizing Maps (SOM) algorithm. They implemented code modifications in the `minisom.py` file and the `examples` directory by developing and refining a Python-based example for the use of SOM on the Iris dataset. The contributions included making the SOM picklable, as well as refactoring the Gaussian, and the creation of visualization methods.

outlier-detectiondimensionality-reductionunsupervised-learningdeep-learningneural-networks

enechange/EnergyDataSimulationChallenge

Dec 2013 - Apr 2016

Challenge by ENECHANGE Ltd.

Role in this project:

Full-stack Developer

Contributions:15 commits, 6 PRs, 4 pushes in 2 years 3 months

Contributions summary:Giuseppe contributed to the project by submitting multiple revisions of an HTML file related to energy consumption visualization, including a notebook file. They implemented front-end visualizations using HTML, potentially with JavaScript. The user also made minor revisions to the presentation of these visualizations. Additionally, the user included a submission for a challenge 1 with a notebook using python and libraries like `numpy` and `sklearn`.

javaenergymodelicaprediction-model

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