Data Scientist Resume

SUMMARY:

Technical professional having 4 years of experience applying data sciences in the domains of energy, retail, human resources, and banking.
Pursuing masters in Data Sciences with research direction along the lines of Convolutional Neural Networks (CNN).
Expertise in using tools like Python, IBM SPSS, Tableau, and Microsoft Azure Machine learning framework as an aid to generate business’ value.
Expertise in applying big data frameworks like Hadoop and Spark to make prediction algorithms on high volume data
Knowledge of applying vectorized operations on textual data to enable the formulation of strong classification models.
Knowledge of using Tensorflow and Keras on visual data for the purposes of image classification.
Knowledge of applying graphical methods on high volume data to enable queue management and resource optimization.
Knowledge of applying ensemble techniques to predict the likelihood of power theft.

TECHNICAL SKILLS:

Python

TensorFlow

C/C++

Selenium

Hadoop

Spark

Django

Linux

R Language

Tableau

MySQL

Mongo DB

IBM SPSS

Microsoft Azure Machine Learning module

EXPERIENCE:

Confidential

Data Scientist

Responsibilities:

Identified high risk physicians as part of compliance monitoring within life sciences
Conducted an in house Data Sciences to inculcate a data driven approach within products and services

Confidential

Data Scientist

Responsibilities:

Responsible to predict hourly queue lengths and waiting times with an accuracy of 86% to enable the bank to optimize its resource and streamline its queue management system.
Scraped business associated social handles on improved coverage and precision rates.
Responsible to in corporate NLP (Natural Language Processing) techniques to generate Twitter ad targeting from Yelp allocated business categories.
Responsible to develop automated insights to help Small Medium Enterprises (SMEs) understand their digital footprint relative to the industry they belong from.
Responsible to add the provision of on - off premise synchronizing on Point of Sale (POS) locations.
Automated the deployment of off-premise POS installations.

Confidential

Senior Data Analyst

Responsibilities:

Conducted data collection, and treatment of 76 mn data points, falling within the realms of insurance, and banking.
Responsible to scrape data and determine its commercialization potentials for the domains of banking, consumer electronics, consumer goods, crime,, grocery, health, insurance, and real estate.
Performed data treatment of Economic Survey, USA totaling up to 1.3 billion data points.
Proposed data product ideas related to income disparity, and public reporting.
Capitalized upon the data potentials to discover relevant markets for tea export in the United States.