Akshara Ponugoti

Master's

Science, Technology and Society

Cybersoft Technologies

Data Analyst

- TX, USA - Created an aggregated report daily for the client to make decisions and help analyze meal pattern trends - Built an internal visualization platform for the clients to view historic data, make comparisons between various issuers, analytics for different bonds and market - The model collects, merges daily data from market providers and applies different cleaning techniques to eliminate bad data points - The model merges the daily data with the historical data and applies various quantitative algorithms to check the best fit for the day - Captures the changes for each market to create a daily email alert to the client to help make better investment decisions - Built the model on Azure platform using Python and Spark for the model development and Dash by plotly for visualizations - Built REST APIs to easily add new analytics or issuers into the model - Automate different workflows, which are initiated manually with Python scripts and Unix shell scripting - Create, activate and program in Anaconda environment - Worked on predictive analytics use-cases using Python language - Clean data and processed third party spending data into maneuverable deliverables within specific format with Excel macros and python libraries such as NumPy, SQLAlchemy and matplotlib - Used Pandas as API to put the data as time series and tabular format for manipulation and retrieval of data - Helped with the migration from the old server to Jira database (Matching Fields) with Python scripts for transferring and verifying the information - Analyze Format data using Machine Learning algorithm by Python Scikit-Learn - Experience in python, Jupyter, Scientific computing stack (numpy, scipy, pandasand matplotlib - Perform troubleshooting, fixed and deployed many Python bug fixes of the two main applications that were a main source of data for both customers and internal customer service team - Write Python scripts to parse JSON documents and load the data in database - Generating various capacity planning reports (graphical) using Python packages like Numpy, matplotlib - Analyzing various logs that been generating and predicting/forecasting next occurrence of event with various Python libraries - Created Autosys batch processes to fully automate the model to pick the latest as well as the best bond that fits best for that market. [O - Created a framework using plotly, dash and flask for visualizing the trends and understanding patterns for each market using the history data. [O - Used python APIs for extracting daily data from multiple vendors. [O - Used Spark and SparkSQL for data integrations, manipulations. Worked on a POC for creating a docker image on azure to run the model [O - Environment: Python, Pyspark, Spark SQL, Plotly, Dash, Flask, Post Man Microsoft Azure, Autosys, Docker [O