Gizem Arpay

Data Analyst @HubX

Istanbul, Türkiye

About

Data scientist with 1.5 years of hands-on experience in predictive modeling, web crawling, and customer analytics. Skilled in Python, SQL (Redshift, Athena, PostgreSQL), NLP, AWS, and Airflow.

Experience

  • Junior Data Analyst at HubX
    Sep 2024 - Present · 1 yr 10 mos

  • Data Science Intern at Getir
    Jun 2023 - Mar 2024 · 10 mos

    • Developed web crawling algorithms using BeautifulSoup and Selenium to analyze over 20 competitor websites, enhanced real-time market research and improved pricing responsiveness. • Fine-tuned and compared BERT-based models for analyzing search queries, provided insights and identified areas for future improvements to ensure robust performance. • Created comprehensive search data marts to calculate search conversion rates using Python and SQL. Optimized complex database queries and achieved a 40% reduction in data processing times.

  • Data Science Intern at TOM
    Jan 2023 - May 2023 · 5 mos

    • Performed customer analytics, including cohort and funnel analysis, used Python and SQL to uncover trends and patterns in customer data. • Worked alongside senior data scientists to develop predictive models, focused on dataset preparation and feature engineering. • Addressed ad hoc data analysis requests from multiple departments, delivered insights to enhance business operations.

  • Intern at BtcTurk
    Jun 2022 - Aug 2022 · 3 mos

    • Analyzed user behavior and developed segmentation strategies to enhance engagement and retention through targeted push notifications. • Conducted market research on industry trends and competitor strategies, supporting business decisions with actionable insights. • Integrated user feedback into product development, enhanced product functionality and user satisfaction.

  • Information Technology Intern at English Home
    Nov 2021 - Jan 2022 · 3 mos

    • Updated customer and product data to ensure data quality using SAP. • Assisted with troubleshooting and resolving technical issues for end users across various departments.