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Data and Machine Learning Engineer, Data Analyst, Teacher
# Data Engineering - Create and maintain data pipelines with dbt, Python, Spark - Model data by using star models, snowflake models, relational models - Develop and maintain a data mesh or a data warehouse # Business Intelligence - Develop and maintain dashboards with Looker, and Looker Studio - Analyse data with SQL, Python notebooks, pandas - Define metrics and KPIs by involving and integrating stakeholders # Machine Learning - Create and maintain ML models with scikit-learn - Create APIs with FastAPI make models available - Design and implement data flows to continuously evaluate and improve ML models
Università degli Studi di Udine
Master's degree, Computer Science
January 1, 2004 – January 1, 2011
Université de Fribourg - Universität Freiburg
Temporary Lecturer ("Chargé de cours")
February 1, 2025 – June 1, 2025
Fribourg, Fribourg, Switzerland · On-site
Université de Fribourg - Universität Freiburg
Temporary Lecturer ("Chargé de cours")
February 1, 2021 – July 1, 2022
Fribourg, Switzerland
SMG Swiss Marketplace Group
Machine Learning Engineer
May 1, 2020 – January 1, 2025
Flamatt, Berne, Switzerland · Hybrid
Swisscom
Data Scientist for Data, Analytics & AI
February 1, 2017 – July 1, 2019
Bern Area, Switzerland
Swisscom
Intern
September 1, 2015 – December 1, 2015
Bern Area, Svizzera
Yahoo! Labs
Visiting Researcher
September 1, 2014 – November 1, 2014
Barcellona, Spagna
Université de Fribourg - Universität Freiburg
Researcher
December 1, 2011 – December 1, 2016
Fribourg, Switzerland
Certificat de participation: Cursus médiation CNV
Association Suisse des formateurs en Communication NonViolente
June 24, 2026 – Present
Attestation de formation: Initiation Partie I à la communication NonViolente
Association Suisse des formateurs en Communication NonViolente
June 24, 2026 – Present
Attestation de participation: Formation à la Communication NonViolente, Initiation 2
Association Suisse des formateurs en Communication NonViolente
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning academia (lecturer, researcher) and industry (ML Engineer, Data Scientist), indicating adaptability to different work environments. The experience with various companies and roles, including a temporary lecturer position, suggests a willingness to take on varied challenges. However, the project section is empty, which limits the assessment of personal initiative and passion projects. The certifications are in NonViolent Communication, which suggests an interest in interpersonal skills, but their direct relevance to a technical cultural fit is indirect.
Soft Skills & Operational Fit
The candidate's experience as a lecturer and researcher indicates strong communication and teaching skills, which are beneficial for team collaboration and knowledge sharing. Coordination of small teams suggests leadership potential. Experience with SAFe indicates adaptability to agile methodologies. However, the provided data does not offer specific insights into stress handling or direct team collaboration effectiveness beyond role descriptions.