Greetings!

Welcome to my website! I have a Master’s degree in Computer Science and have authored a publication on machine learning. I have worked as software engineer and data scientist and I am enthusiastic about pursuing a career in machine learning, deep neural network, and generative AI. My commitment to this journey is evident through my ongoing efforts to enrich my skills and knowledge in this dynamic field. My professional journey has seamlessly blended my technical expertise with a passion for a keen eye for details, and proficiency in tools like Python, SQL, and VBA. My hands-on experience extends across a broad spectrum of data science domains, including classification, regression, clustering, time series forecasting, natural language processing (NLP), and deep learning models. Dive into my portfolio and resume to discover more about my machine learning and AI expertise and how I can contribute to your projects and endeavors.

Portfolio

The primary objective of this project is to forecast significant wave height along the coasts of Ireland. The project encompasses a comprehensive data preprocessing phase, involving data cleaning, feature engineering, datetime index standardization, and stationarity adjustments to ensure the dataset's quality and consistency. The Dataset includes historical wave measurements such as height, direction, speed, sea temperature, and geographical information recorded for 3 years. We aimed to develop a robust predictive model that could provide reliable estimates of wave heights for specific locations over a 3-month period. Leveraging advanced machine learning algorithms, and employing time series techniques, we constructed a model capable of learning intricate data patterns and relationships. Among the tools and techniques utilized were the XGBoost algorithm, STL decomposition, datetime standardization, and resampling. Our developed model exhibited a remarkable capacity to detect hourly time series fluctuations and deliver accurate predictions for a 3-month horizon. Finally, testing and validation processes were carried out to ensure the model's reliability and generalization to unseen data. The successful completion of this project holds immense potential for maritime safety, coastal management, and various ocean-related activities, offering stakeholders valuable insights to make informed decisions based on accurate wave height predictions.

This project serves as a showcase for my Master's thesis which was presented at the CATA conference in 2018. In this work, I used R to create a Machine Learning model to predict the next check-in place only based on places history and with no reference to individual users. To this end, we learned that the check-in data has a high level of noise in location coordinates. The main research objective of this work is how to leverage a noise impact reduction technique to enhance performance of prediction model. We designed and developed our own noise handling mechanism to deal with feature noise. This work represents how the performance of predictors is enhanced by minimizing noise impacts.

Skills

  • Tools

    python, SQL, VBA
    Linux, Tableau
    Scikit-learn, Tensorflow, Keras, Scipy
    Numpy, Pandas
    Matplotlib, Seaborn

  • Data Analysis

    Exploratory Data Analysis
    Data Cleansing
    Statistical Analysis
    Visualization
    Time Series Analysis and Forecast

  • Data Science

    Deep Learning
    Machine Learning Modeling
    Bias and Variance evaluation
    XGBoost and Decision Trees

Experience

Over the course of six enriching years at Amdocs, I had the privilege of holding roles as both a software support engineer and a data analyst. During this time, I had the opportunity to work with a diverse set of tools and technologies, including SQL, VBA, and Python, to effectively manipulate telecommunication data and extract valuable insights from it. Amdocs, as a lead player in the telecommunications industry, entrusted me with various responsibilities aimed at enhancing customer experience, revenue and billing assurance, and providing CRM and OMS software support. These responsibilities encompassed a wide range of tasks and challenges.

One significant highlight of my tenure at Amdocs was the development of an innovative VBA automation solution. This solution proved to be a game changer, significantly elevating data quality standards and automating up to 80% of the data preprocessing steps. As a result, our analytical processes were streamlined, and the quality of our insights was greatly enhanced.

In summary, my time at Amdocs allowed me to contribute meaningfully to the telecommunications industry by leveraging my skills. Through innovative solutions and a commitment to excellence, I played a pivotal role in improving data management and analytical processes, ultimately benefiting both the company and its customers.