Nicola Rapacchiani

Data Analyst/Scientist with a strong foundation in Python and SQL, specializing in transforming complex data into actionable insights. Proficient in data visualization using Power BI and Python libraries. Experienced in automating data processes to increase efficiency and in implementing machine learning models (including Scikit-Learn, TensorFlow, and PyTorch) to uncover deeper patterns and insights.

Passionate about leveraging data to solve real-world problems in finance, marketing, and sports. Eager to contribute to innovative teams and drive data-driven decisions

JUNIOR DATA ANALYST | TELUS INTERNATIONAL

DEC 2023 – MAY 2024

• Conducted in-depth analysis of customer datasets using Python (pandas and NumPy libraries) and MS Excel. Identified the pattern in the rates, frequently purchased items and peak engagement times. This analysis contributed to a campaign that resulted in 15% increase in customer retention in one year.
• Developed scripts in Python on Google Colab or Jupyter Notebook to automate the data validation process. This involved checking for missing values, inconsistent formats and duplicates across tables. This automation reduces drastically the validation time and enabled faster access to clean data.
• Built Power BI dashboards and reports for the marketing team, integrating data from SQL Server or CSV files. Set up interactive visuals to track weekly updates in product category sales and customer demographics.

DATA ENGINEER | DataArt |Internship

JAN 2023 – APR 2023

• Developed and maintained automated data pipelines using Microsoft Azure Data Factory, streamlining the transfer of large datasets (up to 10GB per batch) from Azure Blob Storage (CSV format) to a cloud-based SQL Server.
• Improved data transfer efficiency by approximately 10%, significantly reducing the processing time for data ingestion.