Huseyin Can Minareci
About Huseyin Can Minareci
Huseyin Can Minareci is a Data Scientist at Procter & Gamble with a background in natural language processing, machine learning, and data analytics.
Current Title and Role at Procter & Gamble
Huseyin Can Minareci currently holds the position of Data Scientist at Procter & Gamble. He has been working in this role since 2021 in Warsaw, Mazowieckie, Poland. His responsibilities involve leveraging data science techniques and tools to tackle business challenges and drive insights for decision-making within the company.
Work Experience at Huawei
From 2020 to 2021, Huseyin Can Minareci worked at Huawei as an NLP Developer & Voc Analyst in Warsaw, Mazowieckie, Poland. During his 10-month tenure, he focused on natural language processing and voice analysis, contributing to the development of models and tools to better understand and process human language.
Educational Background and Degrees
Huseyin Can Minareci has a strong academic background. He earned a Master's degree in Data Science and Business Analytics from the University of Warsaw, between 2019 and 2021. Prior to this, he obtained a Bachelor's degree in Economics from Ege University, where he studied from 2012 to 2017. Additionally, he spent a year at the Slovak University of Agriculture, studying Economics from 2015 to 2016.
Technical Projects and Applications
Huseyin Can Minareci has developed a variety of technical projects. Notable projects include the development of a web application for text category recommendation using BERT and frameworks like TensorFlow and Keras, and conducting topic modeling and sentiment analysis on Gamestop tweets utilizing Python libraries such as NLTK and tweepy. He has also created cross-sell prediction models using Random Forest and XGBoost, showing expertise in machine learning.
Automation and Analytical Expertise
Huseyin Can Minareci has demonstrated significant skills in automation and data analytics. He automated COVID-19 reports using RMarkdown, indicating his proficiency in data reporting. He also developed an analytical dashboard using R and Shiny for employee attrition analysis, which is publicly accessible. His projects show a keen ability to leverage data for insightful analysis and actionable reporting.