Ersan Kucukoglu

-Developed reporting solutions for ServiceNow data using SQL, Tableau, ServiceNow Reporting, Looker, and Excel -Utilized Snowflake SQL for efficient data manipulation, demonstrating a strong ability to handle large datasets -Collaborated with a Data Scientist on to develop machine learning models for clustering and sentiment analysis, employing Python for data preprocessing and text analysis -Supported product owners with data analysis, focusing on clear communication and documenting business processes

•Delivered highly skilled end-user support, KPIs with a 92% ticket quality score and 90% SLA compliance rate,avg CSAT score of 4.7/5 •Developed reporting and dashboards to analyze incidents data, identify trends, and drive performance insights •Collaborated cross-functionally streamlining expense reporting and enhancing data accuracy •Performed thorough analysis of employee data using MS Excel and SQL Server, rectifying ID discrepancies and improving card management

• Built Python-based Databricks data product for monthly plastic packaging weight prediction and tracking using advanced time series analysis. • Utilized SQL, Python (including pandas, numpy, PySpark, and plotly) for data cleaning and exploration. • Implemented forecasting models, achieved 64% improvement in the model performance. • Developed SQL Dashboard for analyzing and predicting sales forecasts, enabling optimized plastic packaging decisions.

• Designed offer and cost analysis for projects with procurement, design, and manufacturing collaboration. • Streamlined the process of creating offers and designs for clients by developing a customized solution in Excel, reduction errors and saved 45% time • Created monthly sales and customer reports, uncovering insights to drive business growth and enhance customer satisfaction. • Built monthly sales and customer reports, revealing actionable insights for business growth and customer satisfaction .

Researched data science projects at the Cambridge Center for Data Driven Discovery, participated in a Machine Learning Clinic Session, and attended a statistics course in the Computer Science Department.

Courses: Coding: Data Management and Analysis with R, and Python; Data Analysis (EDA, Prediction, Time Series, Machine Learning); Data Engineering: SQL, Cloud Computing (AWS), Big Data Computing with Apache Spark, Data Science: Machine Learning Concepts, Data Visualization with Tableau, Python Programming, Visualization and Text Analysis, Agile Project Management and Scrum • Full scholarship recipient, demonstrated exceptional academic merit

• Courses: Computer Programming, Transform Techniques with Computer Applications, Basic Information Technologies, Statistics, Microprocessors, Wireless Communications • Received scholarship from Roma Education Fund and Senbas Group