Machine Learning Software Engineer


I am a highly self-motivated Software Engineer with keen interest and passion of applying Machine Learning algorithms and building tools & Big Data solutions to the aviation industry. I strongly believe that "you grow as you learn". I Quit my career as an IT professional to pursue my passion for developing software tools that would be deployed in the aviation industry.
While pursuing my MS degree in Software Engineering at Embry-Riddle Aeronautical University (ERAU), I have completed projects using Machine Learning and Data Mining algorithms. These projects included performing Predictive Analytics to determine Remaining Useful Life (RUL) of a turbofan engine using NASA's Turbofan data set, predicting flight delay by fusing weather data with flight data and predicting trend in the stock price.
While working as a Research Assistant with ERAU, I am developing a big data warehouse for aviation related data accumulated by ERAU over the years. I developed a tool using Python to parse the TFMS data for the FAA project and now working towards presenting a complete Big Data solution for storing, managing and processing such data. A paper for this research was published on Jan 5, 2020 and presented at AIAA SciTech Forum-2020.
Additional projects include developing a web-based desktop application student work collection and assessment for an ABET accreditation process using HTML for front-end UI and Python Flask for backend and database connectivity.
Programming languages: Python, JAVA, XSLT, SQL, HTML,
Python packages: Scikit-Learn, TensorFlow, Keras, ElementTree, lxml, Beautiful Soup, Folium, ipyleaflet, NumPy, Pandas, ipywidgets, Bokeh, Matplotlib
Other Technical: Active Directory (Server 2008 & 2012), Anaconda, Jupyter notebooks, Apache NiFi, Hive, HDFS, Cloudera


Looking forward to work for an aviation company which is research focused, challenges and motivates its employees to work on projects they have never worked on before and looks for people who are ready to do whatever it takes to find a solution and keep things moving, with a supportive and collaborative work culture.

Employment Preferences
Expected Base Salary

**,000 USD / year

Academic Degree

Total Professional Experience

5 years

Startup Experience

no experience

Big-Tech Companies

no experience

Enterprise Experience

no experience
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