Kavana Venkatesh's Linkedin Analytics

Everything I share on this platform is my personal opinion and does not represent the organization that I work for. Data is the new oil! It is incredible to see how data is taking over the world of technology and is enabling making complex business decisions easier by each day. Data Science fascinates me because it is systematic, artistic, involves a diverse set of skills, and is ever-evolving. Data extracts meaning out of the mess and adds value to people's lives. In the journey of finding my true passion amidst innumerable possibilities, I have found that Data Science is what I want my career to be in. It feels right and makes me happy and proud of what I am doing. And so, after completing my bachelor's of engineering in Electrical and Electronics, I pursued and graduated with Master's in Data Science at Northeastern University, Boston. With extensive experience in working on Data Science projects across various domains, I have gained expertise in handling huge amounts of data, building and deploying data pipelines, and analyzing performance by creating domain-based metrics. I completed my Bachelor of Engineering in Electrical and Electronics Engineering at Sri Jayachamarajendra College of Engineering, India, where I was exposed to Machine Learning and Deep Learning techniques. I worked on several projects like designing and optimizing electrical network architectures using my newly attained skills in Data Science. I recently finished my Co-op as a Data Scientist at Fidelity Investments, where I worked with cross-functional engineers to build and deploy large-scale distributed ML models and pipelines to predict trends in financial stock data and maximize expected returns of stocks. I am proficient with Python and R. My skillset also includes Machine Learning (Regression, classification, clustering, dimensionality reduction), Deep Learning (ANN, RNN, CNN, Autoencoders, Transformers, PyTorch, and Tensorflow), Database techniques (MySQL, SQLite, RMySQL, RStudio, XPath), A/B Testing, Hypothesis Testing, Snowflake, Airflow, PySpark, AWS, and Data Visualization (ggplot2, Matplotlib, Seaborn, Tableau). I am still enthusiastically grabbing onto new frameworks and techniques to be a better Data Scientist. In my free time, I write poetry and stories, create new music, or read books, preferably about Philosophy, Psychology, Neuroscience, and deeper aspects of life's beautiful nuances.