Data Science & Marketing Analytics Master's Graduate

Bachelors in Economics and Business Economics

Product Management | Data Analytics | Machine Learning

As a highly analytical and results-driven Data Science and Marketing Analytics graduate, I bring a robust background in Economics and Business Economics, coupled with a deep understanding of data analytics and product management. My expertise lies in the development, deployment, and optimization of machine learning algorithms, aimed at driving strategic decision-making and unlocking value from complex data sets. I possess advanced proficiency in building and visualizing dashboards using industry-leading tools such as Tableau and PowerBI, enabling stakeholders to gain actionable insights and track performance metrics effectively.

My core competence revolves around my exceptional abstract comprehension skills, which allow me to synthesize and interpret various types of data with precision and clarity. This unique ability enables me to bridge the gap between raw data and business strategy, ensuring that data-driven insights are both practical and aligned with organizational goals. I have a proven track record of leveraging these skills in diverse projects, where I have not only contributed to the successful execution of data-driven initiatives but have also led cross-functional teams to deliver impactful results.

• - This is my masters thesis. A study on predicting price movements of crypto currencies
• - This is my Portfolio. A lot of smaller Python related projects are in there!
• - My Crypto Repo. Anything crypto data research related.

• Support Vector Machines (SVM)
• Random Forests (RF)
• Linear Regression
• Logistic Regression
• XGBoost
• Gradient Boosting

• Long Short-Term Memory (LSTM) networks
  • Specialization in time series forecasting
• Artificial Neural Networks (ANN)
• Recurrent Neural Networks (RNN)
• Applications in both regression and classification tasks

• Hypothesis Testing
  • Chi-square tests
  • T-tests
  • A/B testing
• Coefficient Interpretation
  • Linear regression
  • Logistic regression

• Feature engineering
• Model evaluation and validation
• Data preprocessing and cleaning
• Exploratory Data Analysis (EDA)
• Data visualization