I am working as a Senior Data science analyst at Infosys(USA). I have over 2 years experience working in Data science and analytics.
I have a Master's degree in Data science from Indiana University - Bloomington.
I have participated in Kaggle competitions and worked on several projects in Machine learning, Artificial Intelligence and Exploratory data analyses.
I am good in Python, R, SQL, pySpark among many languages and tools.
Srikrishna S.
(812) 955-8935
srikrishna.sridhar@outlook.com
Master of Science in Data Science • May 2019
Relevant Coursework:
Machine learning
Data Mining
Artificial Intelligence
Natural Language Processing
Exploratory Data Analysis
SQL and NoSQL
Social Media Mining
High Performance Big Data Applications
Bachelor of Engineering in Electronic and Electrical Engineering • May 2015
Relevant Coursework:
Fundamentals of Computing and Programming
Data Structures and Algorithms
Object Oriented Programming
Operating Systems
Computer Networks
Transforms and Partial Differential Equation
Numerical Methods
Professional Ethics
Principles of Management
Data Scientist Intern• June 2018 - August 2018
Improved prediction accuracy by 12% using new features created with holidays, outages and transition between different grades of pulp and paper.Assistant System Engineer• May 2015 - Dec 2015
Worked on settling of trades for a Fortune 32 company after successful purchase of stocks.System Engineer/ Analyst • Jan 2016 - July 2017
Used logistic regression to identify possible payment defaulters for a Fortune 130 company.I have around 3 years experience working with Python, R, LINUX and SQL.
I am skilled in PySpark, MongoDB, Tableau, Microstratergy and Git.
Built a recommendation system using collaborative filtering to predict the movie ratings of 100k and 10million users. Designed algorithms based on user’s gender and movie genre, from the ratings given by top 50 similar users using KNN. Achieved 80% accuracy in predicting the movie ratings of users
Recommendation View CodePredicted the revenue of 100,000 restaurants in over 50 cities using Gradient Boosting, KNN, Linear Regression. Performed dimensionality reduction using Boruta to select the best features to predict restaurant revenue. Gradient Boosting achieved Root Mean Square Error of 0.3,thus the overall error in prediction was very less.
Prediction View CodeDesigned maps to predict the total distance , time taken and the paths between any two cities in the USA. Built A*,Uniform, BFS, DFS and IDS search algorithms with distance and time measurements as cost function. GPS co-ordinates and length of roadway between cities in USA were used as metrics for the algorithms. Uniform search algorithm returned the most optimal path between any two cities, within 4 seconds.
Artificial Intelligence View CodeImplemented Random Forest, Logistic Regression and Gradient Boosting to compare performance with Python.
Classified 6899 images from different categories like Airplane, Car, Cat, Dog, Flower, Fruit, Motorbike, Person.
Run-time was reduced by 2000 seconds and 73% accuracy was achieved using Random Forest.
Implemented a Naïve Bayes classifier on a dataset having 32000 tweets, to predict the location from which the tweets were posted.
Effectively handled stop words, special characters and missing words. Achieved 72.5% accuracy, highest among 200 people
Fitted Logistic regression models on the post-election survey response of 64000 adults.
Studied the interaction of answers to immigration questions with gender, race and education.
Analysed the models to understand the switching of supporters between Barack Obama and Donald Trump
Extracted tweets targeting US airlines. Built word clouds. Logistic Regression, Random Forest, KNN, Decision
Tree models were used to predict the sentiment of tweets. Achieved 90% accuracy.
Predicted the favourability of airlines among people based on the sentiments classified.
Krishna was a great resource for Domtar Personal Care and we are very thankful for his efforts. He worked on an important supply forecast problem which will in return help the organization optimize it’s demand side supply chain. He was quick to learn the business and got comfortable coding in R very quickly. He was able to leverage Business Intelligence tools like MicroStrategy to generate great insights for the team. Krishna was hard working, putting in extra effort when asked for and always punctual about time. We all appreciate his professional behavior and him being a great team player. Krishna’s ability to quickly adapt and learn new technologies and also understand statistical models impressed our team.
Source: LinkedInLet's Connect!