➛ Developed and deployed an NLP pipeline in Python using Keras to extract and summarize opinions and feedback from customer product reviews. ➛ Market Mix Modeling using multivariate regression with saturation to visualize ROI &amp; optimize spending ➛ Analysis of the Impact of promotions, advertisements on customer acquisition &amp; LTV ➛ Demand forecasting for supplychain optimization ➛ AB testing analytics to determine the statistical significance of variations and optimize the marketing funnel ➛ Built data pipelines in AWS and GCP to inject data into the data warehouse. ➛ Built &amp; maintained executive summary dashboards in Tableau that summarized KPIs &amp; provided actionable insights which guided high-level data-driven decision making

Data Scientist

Profile: 
https://www.toptal.com/resume/krishna-sai-vootla
Professional Experience:
Currently working for a Health & fitness client in the USA:
1. Helped client with designing & deploying a database for compiling data from multiple API points into a single database
2. Created & deployed data cube for easy & independent data querying.
3. Maintained & created numerous executive summary dashboards


Freelance Data Scientist

Mentored & tutored more than 100 students in Python, R, SQL, C++. I have more than 98% percent satisfaction score from my students. 

For more info check out my profile here: https://www.chegg.com/tutors/online-tutors/Krishna-S-1093188/

Online Tutor

Designed and built a next-generation merchant acquisition tool in R Shiny for credit card business.
Provided pricing analysis for the credit card business.
Built and integrated a minimum revenue model based on customer demographics.

Analyst

Segmented retail customers based on their shopping behavior by using Random Forest.
Designed, built, and deployed end-to-end machine learning pipeline.
Performed marketing analysis of a leading retail company in the US.

Business Analyst

Created automated data pipeline to scrape unstructured data from internal website into a database.
Created and deployed various executive summary dashboards.
Automated data cleaning pipelines.

Senior Software Analyst

Professional Experience:
1. Sentiment Extraction: Created a sentiment classification pipeline for product reviews. Cleaned the text reviews & transformed them into word embedding features. Trained & deployed Recurrent neural network architecture.
2. Multi-Modal Fully Convolutional Network for Semantic Segmentation: Fully convolutional network (FCN-32s) trained to semantically segment forest scene images with RGB and nir_color input images. The project was developed to help unmanned drones in smooth navigation. The model is trained and tested on still images of forest scenes. Intel Edison and Microsoft Kinect were used for proof of concept and prototype creation.

Certifications:
1. Structuring Machine Learning Projects. (Credentials: https://www.coursera.org/account/accomplishments/verify/SWS7ML6DQ89J)
2. Sentiment Analysis in Python. (Credentials:https://www.datacamp.com/statement-of-accomplishment/course/285c1af464d0e83760842e7a17020c72926828f5)

Professional Experience:
1. Market Segmentation for ad Campaign: Built an end to end market segment classifier for each customer based on their shopping behavior. 
2. Sales forecasting for black Friday sale

Certifications:
1. Statistical Learning - Stanford Online. (Credentials: https://drive.google.com/file/d/1NLpvLZmh1M-wUjG4fkxx2LX01Pkr6W7-/view )
2. Python A-Z: Python for Data Science with Real Exercises! ( Credentials: https://udemy-certificate.s3.amazonaws.com/pdf/UC-ZAIQ45JS.pdf )
3. SQL - MySQL for Data Analytics & Business Intelligence ( Credentials: https://udemy-certificate.s3.amazonaws.com/pdf/UC-SE95FTH2.pdf )

Professional Experience:
1. Worked as an Analytics vendor for the leading retail company in the USA. (client has a retail store in every 5-mile radius of the USA, can't reveal the name due to NDA): Created & deployed multiple executive summary dashboards.
2. Part of daily insights team: Helped test client's new business propositions with A/B testing. Designed data pipelines for easier analysis & insights

Certification:
1. Introduction to R ( Credentials: https://www.datacamp.com/statement-of-accomplishment/course/d5f057f64082b4212f5c65f602e8dcc4463f00c3)
2. Intermediate R ( Credentials: https://www.datacamp.com/statement-of-accomplishment/course/9d45665703b6d366794e1ba3a73fbdd3376733de)
3. Data Manipulation in R with dplyr ( Credentials: https://www.datacamp.com/statement-of-accomplishment/course/1d8d86faa76276fa065285f176f21d4f4f1b86c1)
4. Building Web Applications in R with Shiny ( Credentials: https://www.datacamp.com/statement-of-accomplishment/course/b7e148e6ab3c52c66d024bcf8bf3f367b91b4bff )
5. Python A-Z: Python for Data Science with Real Exercises! ( Credentials: https://udemy-certificate.s3.amazonaws.com/pdf/UC-ZAIQ45JS.pdf )
2. SQL - MySQL for Data Analytics & Business Intelligence ( Credentials: https://udemy-certificate.s3.amazonaws.com/pdf/UC-SE95FTH2.pdf )

Part of daily insights team: Created & deployed multiple executive summary dashboards to summarize essential metrics for the busisness

Sample Project: This is a sample app/web-tool that can be used by commercial banks for easy on-boarding of their customers. This app is equipped with all the features that are required for a full blown app.
Link: https://github.com/krishnasaiv/Open-Bank-Account-Online

Machine learning engineer

Krishna Sai Vootla

Fully convolutional network (FCN-32s) trained to semantically segment forest scene images with RGB and nir_color input images.

The project was developed to help unmanned drones in smooth navigation. The model is trained and tested on still images of forest scenes.

Intel Edison and Microsoft Kinect were used for proof of concept and prototype creation.

Personal details

Krishna V.

Summary

Technical skills

Work Experience

Education

Personal Projects