I am a Data Science Intern (Auto ML) at Ascendo AI. I am involved in building and automating 500+ ML models for Flight Data Recorder in production environment using Random Forest, a predictive modeling technique. I have performed feature engineering to yield high predictive accuracy of 98%. Also worked with large time-series datasets to deliver product that saved 16 man hours per week for the team. I have experience in analyzing data and developing models in high quality Python code using ML frameworks and libraries like Tensorflow, scikit-learn, pandas & numPy.
Recently, I was a Graduate Computer Science student at University of Southern California. I have worked as a Research Assistant with Dr. Mahta Moghaddam on SoilSCAPE, a NASA Jet Propulsion Laboratory project. I was responsible for evaluating accuracy of soil moisture using Big Data Management, visualization, analysis and Data mining techniques.
Interests: Inclined to work towards data science, NLP and ML applications in the sectors of social media, healthcare and business intelligence (recommendation systems). I also see myself potentially involved in roles encompassing Machine Learning, Big Data analytics (cloud infrastructure) along with software development.
I have previously worked as a Senior Software Engineer for 2+ years. I have hands on experience in SQL, Amazon Web Services (AWS), Linux, Oracle Database and Shell Scripting, working in an Agile environment.