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Srinivasa Bala Rudraraju

Data Science Professional

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About Me

I am an experienced Data Science professional passionate about solving business problems using exploratory data analysis, statistical modeling and machine learning techniques

Experience

American Express

Data Scientist

  1. Automated the data pipeline, feature selection/engineering and rule generation framework to identify emerging fraud patterns for small business cards using Python, Pandas, Sklearn, Hive, SPRIM and Spark SQL which reduced the fraud loss by $1 million annually
  2. Streamlined and automated external data evaluation using Python, Pandas, SPRIM and Sklearn to speed up the new feature identification process by 4x

Collabera

Data Scientist

  1. Developed predictive models to detect anti money laundering activity using Python, Random Forest and Logistic Regression algorithms which would help save the operational costs by 50%
  2. Built enhanced name matching for identifying third party wires using NLP\text mining techniques in Python to reduce the false alerts by 30%
  3. Developed a free form text parser tool to identify tax haven countries using Python regex to improve the quality of the alerts by 20%

J P Morgan Chase

Lead Data Analyst

  1. Analyzed the operational data of critical data warehouse using SQL, Python and Shell Scripting to reduce the overall incident count by 50%
  2. Forecasted the utilization and capacity metrics using regression techniques to reduce the operating cost by 30%

Accenture

Senior Software Engineer

  1. Designed and developed scripts to upgrade monitoring framework using Perl and shell scripting to reduce the incident count by 40%
  2. Established the automation framework for cleaning, validating, and processing large amounts of test data using SQL and VBSCRIPT to reduce the manual effort by 70%

Education

Arizona State University

August 2015 - May 2016

Master of Science in Business Analytics

Master of Science in Business Analytics at W P Carey School of Business is jointly hosted by the Department of Information Systems and Supply Chain with an emphasis on the below core areas in Analytics:

  1. Database Management Systems - SQL, Data Modeling and Data warehousing concepts using MySQL.
  2. Data Visualization/Reporting of data using Tableau and IBM Cognos.
  3. Exploratory Data Analysis using Statistics and Probability in StatTools, R and SAS.
  4. Machine Learning techniques using IBM SPSS, Azure ML and Python - Scikit Learn.
  5. Optimization on Linear/Non-Linear Models and Simulation Modeling using Excel Solver.
  6. Big Data on Hadoop, Recommendation Systems using Python, Graph Theory and Streaming using Kafka.
  7. Marketing Analytics using R.
  8. Case studies on Business Analytics Strategy across various domains in the industry.
  9. Capstone Project to devise an end-to-end solution for a real-world problem.
  10. Data Driven Quality Management in coherence with six sigma process.

Malaviya National Institute of Technology

August 2002 - May 2006

Bachelor of Technology in Electrical Engineering

As part of undergraduate education in Electrical Engineering, I was well-trained in the areas of Electrical Engineering areas such as Electrical Machines, Network Theory, Electronic Devices and Circuits, Electrical Measurements, Control Systems, Power Electronics and Power Systems and Computer Engineering areas such as Procedural Programming using C, Object Oriented Programming using C++, Computer Systems Architecture and Organization, Microprocessors, Switching Theory and Logic Design and Numerical Methods/Mathematics.

Projects

MSBA Capstone Project - Home Depot Product Search Relevance

Led a team of 4 members to automate the prediction of Home Depot Search Relevance scores by building machine learning models using Text Mining, NLP, Pandas, NumPy and Scikit Learn modules in Python to obtain a rank in top 20%.

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Platform Testing of Machine Learning Algorithms

Developed machine learning models in Python Scikit-learn for comparing the performance of the bi-class and multi-class classification algorithms such as random forest, decision forest, support vector machines, logistic regression and neural network with other ML Platforms on research datasets. Publication under review by INFORMS Journal on Computing (IJOC).

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Platform Testing of Machine Learning Algorithms II

Extended the research work to develop machine learning models using MLlib library in Spark with hyper-parameter optimization on the research datasets by using Databricks and AWS S3 platforms for executing the models.

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AirBNB Recruitment Challenge

Implemented classification techniques such as XGBoost in Python to accurately predict new user booking country in Airbnb.

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Skills

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