Data Analyst

VIJAYENDRA VASHISTH

Data Scientist +1-562-***-****, +918*********

DETAILS

+918*********

***************@*****.***

SKILLS

Database & Cloud: MS SQL,

MongoDB/NoSQL, Web Scrapping,

AWS EC2, PostgreSQL

Supervised Machine Learning:

Linear Regression &

Regularisation, Logistic Regression,

K-Nearest-Neighbors (KNN),

Decision Trees, Random Forest,

Naive Bayes, Support Vector

Machines (SVM)

Unsupervised Machine Learning:

K-Means Clustering, Natural

Language Processing, Topic

Modeling, Principle Component

Analysis (PCA)

Data Visualisation: Tableau, IBM

Cognos, Matplotlib, Plotly, Seaborn

CODING & TOOLS: Python, SQL,

Flask, IBM SPSS, BASH

Python Packages: Pandas, Numpy,

Scikit-Learn, BeautifulSoup,

Selenium

LANGUAGES

English

Hindi

PROFILE

Data Scientist with a passion for finding the narrative behind data and telling the story. Able to solve business problems through analytical methodologies and programming. Passionate about constant improvement through lifelong learning and Newton's First Law. EMPLOYMENT HISTORY

Data Scientist at Ericsson, Noida

March 2017 — December 2019

Provided accurate and tailored data research, statistical analysis, and trend analysis to help identify potential business obstacles and prepare solutions for different telecom networks. Key Performance Indicators Forecasting:

• Forecasting crucial KPIs like Drop Call Rate, Call Setup Success Rate, etc for the next 5 days to plan preventive measures to avoid degradation

• Modeling techniques used: Time Series Forecasting using Prophet

• Visualization: IBM Cognos, Tableau

Battery Autonomy:

• Predicting the duration of battery support on sites and compare to mains power outage to avoid the generation of Trouble-tickets or deployment of man-power in field

• Modeling techniques used: Linear Regression

EDUCATION

Data Science BootCamp, Metis, San Francisco

January 2020 — March 2020

12-week immersive Data Science BootCamp. Created five end-to-end projects utilizing real-world data. Select projects include:

Saving Kangaroos with Computer Vision:

• Trained a model to detect and identify Kangaroos in images and videos

• Used Neural Nets, Mask RCNN, and OpenCV

Natural Language Processing of Tweets:

• Classifying whether or not people are reporting emergencies and disasters in their tweets

• Used NLP and Topic modeling for classification

Predicting Life Expectancy of a Country:

• Scrapped data from two distinct sources using Beautiful Soup and Selenium

• Modeling Techniques used: Linear, Ridge and Polynomial Regression Image Classification - whether a room is Clean or Messy:

• Created a PostgreSQL database to host data running on AWS EC2 instance

• Modeling techniques included: Logistic Regression, Random Forest, and K-neighbors B.Tech. Electronics and Communication, Dr. A.P.J. Abdul Kalam Technical University, Greater Noida

August 2011 — July 2016

First Division 65.04%

LICENSES & CERTIFICATIONS

Introduction to Deep Learning with OpenCV, LinkedIn Learning March 2020

Learning Git and GitHub, LinkedIn Learning

March 2020

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