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DESCRIPTION OF MY JOB DUTIES DURING CPT EMPLOYMENT:
Created an aggregated report daily for the client to make investment decisions and help analyze
market 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 are 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.
Created a framework using plotly, dash and flask for visualizing the trends and understanding
patterns for each market using the history data.
Used python APIs for extracting daily data from multiple vendors.
These job duties are directly related to my current course of study.
Course Name: Organ Leader & Decision Making
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Course Name: Operational Excellence
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Course Name: Analyzing & Visualizing Data
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Course Name: Cloud Computing
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Course Name: Intro to Data Mining
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