I am a data scientist with over five years of experience dedicated to using data to solve complex and challenging business problems with innovative, data-driven solutions.
I have collaborated with various organizations, focusing on
data-driven problems including product segmentation, sales forecasting, and developing recommendation systems. My approach combines a deep analytical foundation with a creative mindset to deliver impactful outcomes.
My academic background is in Industrial Engineering, which I studied at
Sabancı University, one of the best universities in Turkey. There, I graduated first in my class with a 3.93 GPA during my Bachelor’s program and achieved a 3.95 GPA in my Master’s. Throughout my studies, I served as a Teaching Assistant for several courses, including Decision Analysis, Operations Research, and Production Systems. My projects with Dr. Murat Kaya during both my Bachelor's and Master's studies have significantly shaped my professional approach. You can access my Master’s thesis, involved developing data-driven processes to determine the finished goods inventory levels and associated production decisions for a tire manufacturer.
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I am proficient in a range of programming languages and tools that are crucial for data analysis, data visualization, and model building, including Python, R, and SQL. My expertise also extends to advanced statistical methods and machine learning, which enable me to extract valuable insights from complex data sets.
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Personally, I am passionate about sports, exercise, and maintaining a healthy lifestyle. Engaging in activities such as rowing, running, soccer, CrossFit, and calisthenics not only keeps me energized but also inspires my professional endeavors. This commitment to health and fitness contributes significantly to my productivity and success, both personally and professionally.
Yandex Search Turkey
2024 - Present
I focus on analyzing search query patterns and user behavior to improve search quality and user satisfaction. My work involves mining large-scale search logs, clustering queries to uncover emerging trends and user intents, and developing dynamic dashboards to monitor key performance indicators (e.g., DAU, CTR).
I collaborate closely with product managers and developers, delivering actionable insights that guide feature development and improvements to the search engine results pages (SERPs). I use Python, SQL, and statistical analysis to design experiments, validate hypotheses, and support data-driven decision-making across the Search organization.
Afiniti
2022 - 2024
Brisa
2020 - 2022
Unilever
2018-2020
My goal was to enhance Unilever's forecasting models by integrating human expertise with machine learning, creating a more balanced and precise forecasting system.
I created a new hybrid system to strategically manage Unilever's inventory by distinguishing which products should be handled by machine learning algorithms, which should be directly managed by human input, and which required a mixed approach.
I worked on enhancing customer-agent interactions to boost customer retention. My primary responsibility involved data mining and developing a machine learning model to support agents in presenting the most suitable options to customers after their initial interaction.
I used Python, R, and SQL, drawing on broad datasets containing details of customer interactions and agent activities. My focus was on predicting customer preferences and likely outcomes effectively.​
Philip Morris SA
2018
I developed robust sales forecasting methods for all products and retailers, essential for strategic business planning.
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My project involved designing a data-driven website to predict sales over a six-month period using 18 months of historical demand data. To achieve accurate forecasts, I utilized various data mining techniques, including Power, Logarithmic, Exponential, and Polynomial Regression methods.​