Description

I am a strategic leader in Data Science and Data Engineering with a passion for driving organizational growth and leveraging data-driven strategies. With a proven track record of leading teams in delivering innovative solutions, I have successfully built data lakes, streaming platforms, and developed predictive models. I am experienced in collaborating with business leads and stakeholders on high-impact projects, and I possess strong technical skills in cloud technologies, modern data stack, streaming platforms, databases, data warehouses, data visualization, and reporting.

Languages

Italian
Native or bilingual
English
Native or bilingual
French
Native or bilingual

Workplace preferences

Can work on-site

London (up to 50km)

Hyde Group
Head of Data Engineering
REAL ESTATE
October 2021 - December 2022 (1 year and 2 months)
London, UK
Led a talented team of data engineers, technical delivery managers, and data analysts in a multi-year digital transformation journey at The Hyde Group, a prominent social housing company, while also collaborating with data scientists on advanced analytics.

Pioneered the development and implementation of a sophisticated data integration platform using Confluent Kafka, AWS services, and Salesforce, significantly improving service delivery for clients who rented or owned homes.

Established an innovative analytical framework by combining a data lake, AWS Redshift, and PowerBI to provide advanced insights and data-driven decision-making capabilities.

Owned and maintained data models and architecture design, ensuring seamless integration with the company's broader digital transformation strategy.

Created a comprehensive data roadmap, aligning it with company objectives, and successfully gained support from key stakeholders and directors.

Fostered enhanced customer experiences and operational eficiency through the digital transformation, resulting in streamlined processes, reduced response times, and personalized services for Hyde's clients. This, in turn, solidified The Hyde Group's position as a customer-centric and innovative social housing provider.
Technologies: Agile Methodologies Data Strategies Data Architecture Senior Stakeholder Management
Agile method Microsoft Power BI Apache Kafka Data Strategy
VIOOH
Head of Data Science and Engineering
DIGITAL AND IT
October 2017 - October 2021 (4 years)
London, UK
Industry: Supply Side platform for Digital Out of home backed by JCDecaux Group

Led the data science and engineering team at VIOOH, an innovative digital out-of-home (DOOH) advertising supply-side platform, driving the development of advanced pricing models, demand forecasting, and image safety classification systems...

Worked with engineering teams to design and implement a robust streaming platform (Kafka) and data lake, enabling eficient data processing and storage, which significantly enhanced the capabilities of the data science department.

Developed a cutting-edge algorithm for advertising inventory allocation, which improved occupancy and powered 25% of worldwide campaigns.

Leveraged time-series analysis, classification algorithms, and AWS Rekognition to deliver intelligent insights and optimize advertising placements, resulting in increased customer satisfaction and revenue growth.

Developed and implemented an analytics platform based on AWS Quicksight for the larger business, empowering stakeholders to make data-driven decisions and gain valuable insights into advertising performance and trends.

Cultivated a data-driven culture within the organization, promoting knowledge sharing and providing training to colleagues on data science techniques and best practices. Technologies: Machine Learning Predictive models Confluent Kafka AWS Rekognition AWS Quciksight
Machine learning Kaf AWS AWS Quicksight Predictive Models Scikit-learn
Vodafone UK
Senior Data Scientist
TELECOMMUNICATIONS
June 2016 - October 2017 (1 year and 5 months)
London, UK
Led a team of 4 ofshore data scientists, focusing on customer-centric innovation, predictive modelling, and enhancing the customer experience at Vodafone.

Migrated and revamped existing SAS algorithms, implementing a more eficient and scalable Python-based system while working closely with the Teradata warehouse for data extraction and processing.

Developed and deployed machine learning algorithms to identify customer churn patterns, enabling the imple mentation of targeted retention strategies that significantly reduced churn rates. Integrated the algorithm with Device and plan recommendations

Fostered cross-functional collaboration with marketing, finance, and operations teams, driving data-driven decision-making and empowering team members to leverage data insights in their daily tasks.
SAS Python Scikit-learn XGBoost Teradata