Data scientist Resume

SUMMARY

Master’s prepared Data Scientist with 2+ years of experience as a Data Scientist and QA (Data) Engineer at a major investment/financial firm, seeking to leverage my technical, engineering and communication skills to obtain a Data Scientist/ Data Analyst position.

TECHNICAL SKILLS

Technical: Python, SQL, C++, R, UNIX, MATLAB, C, Shell Scripting, HTML/CSS

Databases: Oracle, MySQL, NoSQL

Tools: /IDEs/ Frameworks: PyTorch, Google Cloud Platform, Flask, Tableau, Git, Jenkins, Pytest, scikit - learn, Numpy, Pandas, NLTK

PROFESSIONAL EXPERIENCE

Data scientist

Confidential

Responsibilities:

Decreased manual effort from 42 hours to 15 mins by developing a Machine Learning framework for classifying funds
Extracted data and built, compared, and evaluated models - Logistic Regression, Decision Tree, Random Forest, SVM, Gradient Boosting, LSTM, RNN
Generated a 96% accurate model which was automated, deployed and maintained in production
Created a dashboard using a Python web framework (Flask), HTML and CSS which is used by business to visualize the fund data
Performed quantitative analysis on risk and interest rate factors of portfolio to find factors impacting the market movement
Eliminated factors with high correlation by applying regression on the residual returns
Evaluated risk over assets by analysing percentage of investment loss due to different factors

Graduate Teaching Assistant

Confidential

Responsibilities:

Increased automation suite by 200% creating more than 800 test scripts using Python, SQL and Java
Manipulated data and provided exploratory analysis through visualizations using statistical software (R and Python)
Understood the specifications for Data Warehouse ETL Processes and interacted with the data analysts and the end users for requirements of application responsible to manage more than 27 million customer investments
Monitored key metrics and built reports providing root cause analysis of technological issues, gaining 100% customer satisfaction