Dinesha Dissanayake

WORK HISTORY

EDUCATION

ABOUT DINESHA DISSANAYAKE

I am a dedicated professional with a strong foundation in statistical analysis, data science, programming, and machine learning. Committed to delivering excellence, I excel in applying data-driven solutions to real-world problems and uncovering valuable insights. With a keen interest in groundbreaking research, I thrive in both independent and collaborative environments, prioritizing effective communication and fostering teamwork. My creativity, ambition, and attention to detail ensure high-quality results that contribute meaningfully to teams, organizations, and the academic community: • Academic Excellence: Successfully completed a Master\'s degree in Statistics, while being honored as a Uppsala University Global Scholarship recipient. Additionally, holding a First-Class Honours Bachelor\'s degree in Statistics, I showcase a consistent commitment to academic excellence. • Internship at OCTAVE John Keells, Colombo, Sri Lanka-Data Science Project (Cab Use Case): Analyzed cab service data in Colombo to extract key insights for business improvement. The project included predictive modeling to improve taxi fare estimation-Research Project (AutoML and Feature Engineering Tool Evaluation): Conducted an in-depth comparison of various AutoML and feature engineering tools, and successfully authored a survey paper. • Practical Teaching Experience: Formerly served as a Teaching Assistant at the Faculty of Science, University of Peradeniya, where I guided students through Statistics and Data Science practical sessions, fostering an inclusive learning environment. • Other Data Analysis Projects: Led research projects encompassing Attitudes towards immigrants in Sweden, Mortality Analysis of trees of a Sri Lankan forest reserve, CO2 Emission Prediction in Canadian vehicles, Big Five Personality Trait Analysis, Customer Segmentation Analysis, and Predictive Modeling. My expertise spans Bayesian Linear Regression, hierarchical modeling, clustering, and Log-linear analysis, showcasing a comprehensive understanding of statistical methodologies and predictive modeling. • Professional Skills: Proficient in statistical analysis tools such as R, RStudio, Python, Jupyter Notebook, PyCharm, C along with Microsoft Office, MySQL, and documentation tools like TexStudio and Overleaf. Driven by a goal-oriented approach, I aim to leverage my academic strengths, hands-on experience, and a strong desire for continuous learning to contribute effectively as a Data Analyst or Researcher in an innovative and dynamic environment.