SRIVATHSA CHELUR SREEDHARA

SOFTWARE & DATA SCIENCE

CONTACT

adcgjf@r.postjobfree.com

312-***-****

Chicago, IL

linkedin.com/in/srivathsacs19

github.com/srivathsacs

PROFILE

Aspiring data scientist with background

in software engineering and expertise in

machine learning, distributed computing

looking to make an impact into decision

making process for companies with data

driven approaches.

EDUCATION

2019

ILLINOIS INSTITUTE OF TECHNOLOGY

[CHICAGO, IL]

Master of Computer Science

2017

DR.AMBEDKAR INSTITUTE OF

TECHNOLOGY [BANGALORE, KA]

Bachelor of Engineering in

Computer Science

MANAGEMENT SKILLS

• Agile Development

• SNOW, Git, Excel, Powerpoint

TECHNICAL SKILLS

• Programming Languages: Python,

SQL, PySpark, R

• Machine Learning, Deep Learning

• Statistics and Probability

• Cloud: AWS, Microsoft Azure

• Visualization: Tableau, Power BI

• Distributed Computing: Spark,

Kafka, Hadoop, ETL

• Databases: MySQL,Postgres,Redis,

Big Data NoSQL

EXPERIENCE

March 2020-Present

Research Assistant Illinois Institute of Technology Current Project Image Recognition

• The task is to classify the images using baseline CNN model with Image Augmentation using Keras, and fine tuning the model to perform better.

• Transfer Learning will be performed using VGG16 model by Google to further improve the accuracy of the fine tuned CNN model. October 2019- March 2020

Software Engineer Tata Consultancy Services Client-AbbVie

• Created reports and visualizations in SNOW, which helped client in better management of more than 600 incidents/SLAs/service tasks amongst various applications every month.

• Performed basic Salesforce SOQL operations, ran reports in Veeva Vault and analyzed the patterns inside literature documents, that solved a major issue, which helped the client in saving approximately $80K per annum. July 2019- October 2019

Research Assistant Illinois Institute of Technology Past Project Marketing Segmentation Analysis

• Worked on historical sales data to devise marketing strategies, by segmenting products based on zones, using Docker, Redis Enterprise.

• Retrieved data to Tableau and performed marketing analysis by building dashboard and helped improving the revenue by 8%.

PERSONAL PROJECTS

Customer Churn Prediction

• Predicted the customers who were at high risk of leaving the bank using baseline ANN model using Keras, and achieved accuracy of 82%.

• Performed fine tuning, and achieved an improved accuracy of 86%, which was 4% improvement over baseline ANN model.

Predictive Analysis on Customer Shopping Behavior

• Predicted the shopper’s likelihood to return to the store based on the past shopping behavior.

• Stored data in AWS S3 bucket, migrated to AWS EC2, and predicted using RFM model in Python, that helped company in customer retention by 36%. Crime Data Prediction Analysis

• Predicted the major factors that will affect the crime rate using Machine Learning models, achieved 81% as the best accuracy using random forest

• Performed hyperparameter tuning on random forest model and achieved improved accuracy of 84%, which was 3% improvement over base model. Real Time Twitter Sentiment Analysis(Ongoing):

• Building an ETL pipeline to perform sentiment analysis using NLP on live tweets using Spark Streaming(PySpark),Apache Kafka in Linux.

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