cv
Basics
| Name | Leonardo Pacciani-Mori |
| leonardopaccianimori@gmail.com | |
| Location | Padua, Italy |
| Profiles | |
| Summary | After acquiring a solid data analysis experience in academia, I am looking for an opportunity as a Data Analyst / Data Scientist in a dynamic team where I can contribute with my skills and competences in data analysis and machine learning to support strategic decisions by providing actionable, business-driven data insights and contribute to the success of a company. Thanks to my past experiences and my independent projects, I developed a strong attention to details and problem-solving abilities, which I want to apply in a practical, result-oriented business context. |
Experience
-
2021-03 - 2025-03
University of California, San Diego - Researcher and Data Analyst
I contributed significantly to my group’s research portfolio, working on biological physics, bacterial physiology and ecology.
Main duties and resppnsibilities
- Data-driven experiment design
- Lab data collection (HPLC, plate reader)
- Quantitative data analysis (Python, Jupyter; numpy, pandas, matplotlib)
- Mathematical modeling of lab data (statistical fits with scipy)
- Development of Machine Learning algorithm for biological data (clustering algorithms)
- Data reporting
- Presentation of research results at international conferences with multiple stakeholders
-
2019-04 - 2019-10
Harvard University - Researcher
I have spent six months as a visiting graduate student in the lab of Andrew Murray, supervised by Andrea Giometto (now Assistant Professor at Cornell University), working at the interface of bacterial physiology and ecology.
Main duties and responsibilities
- Data-driven experiment design
- Lab data collection (flow cytometer) & analysis (Python, Jupyter; numpy, scipy, pandas, matplotlib)
- Mathematical modeling of lab data (descriptive statistics and regression analysis with scipy)
- Data reporting
Skills
| Coding skills | |
| Python | |
| SQL | |
| noSQL | |
| C++ | |
| Linux | |
| Shell scripting | |
| Mathematica | |
| R |
| Professional skills | |
| Data analysis and visualization, | |
| Data pipeline development, | |
| Data workflow automation, | |
| Task dependency management, | |
| Mathematical modeling, | |
| Machine Learning models development, | |
| Deep Learning/AI models development, | |
| Webscraping & data mining, | |
| Dashboard creation, | |
| Database management & administration, | |
| Data warehousing, | |
| Use of version control systems, | |
| Use of Big Data frameworks |
| Soft skills | |
| Project management | |
| Teamworking | |
| Communication & public speaking, | |
| Organizational skills, |
| Python Library Toolbox | |
| numpy | |
| scipy | |
| pandas | |
| statmodels | |
| matplotlib | |
| seaborn | |
| scikit-learn | |
| tensorflow/keras | |
| beautifulsoup | |
| sqlite3 | |
| sqlalchemy | |
| pymongo | |
| airflow |
| Data Science Toolbox | |
| MS Excel, Word and PowerPoint | |
| Git and GitHub | |
| MySQL | |
| PostgreSQL | |
| Apache Airflow | |
| REST APIs | |
| MongoDB | |
| Tableau | |
| Jupyter | |
| Hadoop | |
| Spark |
Certificates
| IBM Data Engineering | |
| IBM on Coursera | |
| 2024-07-23 |
| IBM Machine Learning | |
| IBM on Coursera | |
| 2024-06-16 |
| IBM Data Analyst | |
| IBM on Coursera | |
| 2024-04-15 |
| IBM Data Science | |
| IBM on Coursera | |
| 2024-03-18 |
Education
-
2017.10 - 2020.12 Padua, Italy
Ph.D. in Physics
University of Padua
-
2015.10 - 2017.09 Padua, Italy
M.Sc. in Physics
University of Padua
-
2012.10 - 2015.07 Padua, Italy
B.Sc. in Physics
University of Padua
Languages
| Italian |
| Native speaker |
| English |
| Fluent |
| Spanish |
| Fluent |
| Japanese |
| Beginner |