Internal Information

Ashesh Shahi

adjo8p@r.postjobfree.com https://www.linkedin.com/in/ashesh-shahi-01b37418b/ 913-***-**** Sponsorship Not Required

SUMMARY

Data Engineer and machine learning enthusiast with strong statistics background and 1+ years of experience in data processing, data visualization and building machine learning models to solve challenging business problems. December 2020 graduate, actively looking for opportunities in the field of Data Science.

KEY SKILLS

• Data Cleansing & Transformation • Statistical & Data Analysis • Feature Design & Implementation • Solution Delivery

• Machine Learning • Mathematical Programming • Requirement Gathering & Translation TECHNICAL SKILLS

• Languages: Python, C, C++, Java, JavaScript, HTML5, CSS3, SPL, Bash

• Databases: MySQL, MongoDB, SQL

• Analytics tool: Spark, Panda, Scikit, Numpy,Matplotlib, Excel, Tensorflow, NLTK,

• Tools and Platforms: Spyder, Jupyter Notebook, Google Colab Notebook,MATLAB, Hadoop, AWS, GCP, Tableau, Splunk, Jira,VersionOne, Nodejs,React,Atom, Git, ServiceNow WORK EXPERIENCE

Allstate Insurance, Charlotte, US May 2020 - Present Splunk Data Engineer

• Automated the collection, indexing and alerting of machine data that’s critical to applications’ operations

• Onboarded new data sources, extracted and parsed the relevant data, and developed meaningful ways to visualize it

• Administered and monitored Splunk infrastructure to recognize bad searches in order to manage overall health of Splunk

• Developed and customized complex Splunk queries to optimize queries’ performance used in dashboards and alerts

• Responsible for maintaining and updating Splunk internal documentation, including data ingestion, alert as well as dashboard creation documents

• Worked collaboratively with team and clients to gather requirements for design, development and implementation of data engineering processes

PROJECTS

Intel Image Classification

• Used Intel image dataset from Kaggle, resized the image, converted the images and labels into integers

• Used Image augmentation technique to better train the model

• Created deep learning predictive models with and without using the transfer learning for image classification

• Used stochastic gradient descent optimization method and improvised it by introducing exponential momentum decay

• Used accuracy_loss graph for model evaluation and achieved 87.4 % accuracy Prediction of the movie rating

• Uploaded IMDB dataset from Kaggle on AWS storage(S3) and used PySpark on databricks to analyze and explore data

• Created a predictive model using linear regression, decision tree, random forest using mllib using unconventional predictors to predict how well a movie would perform before being released

• Build application using Django to predict real time IMDB score using decision tree model Database Project Hospital Management System

• Developed ER Model, Logical Design, Physical Design for a Hospital Management System

• Created a database in MySQL where patients can book their appointments with doctors

• Created indexes and stored procedures for faster query processing

• Created events followed by triggers that update, delete, and insert after event occurs Spam Detection Through Naïve Bayesian Technique Algorithm

• Created bag of words using 5000 emails and perform TF-IDF analysis to evaluate importance of word to an email in the corpus

• Used multiple classification models like Logistic regression and Naïve Bayes Classifier to classify emails as spam or ham (not spam)

• Used precision and recall value for model evaluation EDUCATION

THE UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE, USA Aug 2019- Dec 2020 Master of Science in Computer Science with Concentration in Data Science BIRLA INSTITUTE OF TECHNOLOGY – MESRA, INDIA Aug 2015- May 2019 Bachelor of Engineering in Computer Science & Engineering