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Data Scientist Resume Example

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DATA SCIENTIST
Professional Summary
  • 5+ years of experience as a Data Scientist which includes data analysis and detail-oriented Data science professional with proven record of successes in data collection, manipulation, analysis and deep learning model building
  • Demonstrated expertise in decisive leadership and in delivering research based, data driven solutions that move organizations vision forward.
  • Proficient in data mining tools like Python, SQL, SAS, Big data hive, spark and Excel.
  • Experience with Data Analytics, Data Reporting, Ad-hoc Reporting, Graphs, Scales, Pivot Tables and OLAP reporting.
  • Implement and practice Machine learning techniques on structured and unstructured data with equal proficiency.
  • Create executable python models for the production and monitor performance using tensor board
  • Performing ETL operations using PostgreSQL, MySql, Netezza across multiple sources into Hadoop framework.
  • Proficient in requirement gathering, writing, analysis, estimation, use case review, scenario preparation, test planning and strategic decision making, test execution, test results analysis, team management and test result reporting.
  • Implemented Systems & tools to support Data Management, Big Data and IT Metrics that helped executive management in their decision making.
  • Taken the initiative of training and helping the freshmen joining the organization.
  • Within a span of one and half year I was elevated from Career level 13 to 11 in Accenture Consulting
Skills

Analytical Skills:

  • Random Forests, AdaBoost, Gradient boosting, Linear Regression, Non-Linear Regression, Logistic Regression, Multiple Regression, Factor analysis, Multi-Dimensional Scaling and Discriminate Analysis Relationship Analysis using Correlation, Cross Tabulation and Chi-Square Analysis, CNN, MaskR CNN, Fast R CNN,Yolo object detection, Auto-Encoders,Isolation forest, LSTM, DNN

Analytical Packages:

  • SAS (Base SAS Certified, SAS/SQL, SAS/GRAPH, SAS/ODS, SAS/Macro), Advance SAS, SPSS, numpy, Pandas, Scikit – Learn, Scipy, matplotlib, Tensorflow, Keras, Pytorch, Elmo, Berth, Advance MS-Excel, Tensorboard, Statistical models

ETL & Reporting tools:

  • SSIS, SSRS, SSAS, BIDS, DTS, Business Objects, Informatica 8.x/9.1, Tableau Reporting, Clementine, Advance SQL, Big Data Hadoop, Hive, Pig, python, spark, pyspark, MySql, IBM Netezza
Work History
Data Scientist09/2018 to Current
Ericsson, San Jose, IL

Situation : Identify attacks in IoT devices
Task : Build an anomaly detection model using machine learning or Deep learning models
Action : Stimulated IoT behavior using the sample data and performed feature engineering to increase the performance of the model. Built auto-encoder, robust auto-encoder, isolation forest in unsupervised learning and random forest, gradient boosting in supervised learning models.
Result : The model predicted IoT network attack with 92 % accuracy after feature engineering using the combination of both supervised and unsupervised learning models

Situation : To detect the utility poles on the streets for deploying 5G radio devices
Task : Built an image recognition model to detect utility poles from street view images
Action : Downloaded 10 thousand street view images from bing and created a training dataset. Built CNN model using Resnet50 architecture and weights to detect utility and streetlights in the images. Performed active and transverse learning to train and test the model
Result : The model was able to predict the utility pole with 90 % recall after tuning the hyper parameters.

Data Science Analyst03/2018 to 08/2018
Oriental Trading Company, Omaha, NE

Situation : To identify the most valued customers
Task : Identify a methodology to create a metric to calculate the customer's value
Action : Created a customer lifetime value metric (LTV) by assimilating marketing expenses, mail campaigns and customer purchases. Created product LTV to identify the important products and manage the inventory efficiently. Perform A/B testing to understand the impact of promotions
Result : Increased the coupon code utilization by 15% and increased the sales by 5% in the Q2'2018

Situation : Identify the areas(/region/county/state) to improve sales of list of products
Task : Build the ML model to predict the sales and also to identify the important feature
Action : Created a regression and logistic regression models to improve the sales and churn. Perform recursive feature elimination with cross validation (rfecv) to identify important features and to improve the model performance. The model is compared with RMF (Recency Frequency Monetary Value)
Result : Model was able to predict the sales with 89% of accuracy and identified the areas to improve the sales.

HR Data Analyst Intern05/2017 to 11/2017
Marriott, Omaha, NE

Situation : To reduce the attrition of the employees
Task : Built a ML model to identify the areas to improve the attrition
Action : Collect the data from multiple sources, prepared required data for analysis. Created multiple ML and DL models to identify the areas affecting the churn. Created the benchmarks for data collection and reports from the employee feedback.
Result : Able to reduce the attrition by 5%, created and automated the report for regular validation

Senior Modeling Analyst 11/2013 to 07/2016
Accenture, Hyderabad, Telangana

Zero Based Budgeting (ZBB)
Situation: To create a budget using ZBB concept
Task: Built ML model to forecast the budget and reduce the expenditure of the company, monitor the expenditure on a weekly and monthly basis
Action: Create the dashboard using Tableau to create an annual budget and periodic forecast/outlook and Generating insights. Built theARIMA model to create a time series forecast to predict the budget. Scrutiny of General Ledger on a monthly basis and do a financial analysis o
Result : Reduced the company's expenditure by 1 million dollars and successfully able to monitor the budget
Data Management in the life Sciences Industry

Situation: Create an incentive plan health care, representatives
Task: Built data pipeline to collect data from multiple resources and create a data management model to calculate incentive
Action: Develop a SAS data pipeline to integrate data from multiple resources and check for data compatibility. Develop dashboards to integrate the data pipeline to show the updates of the incentives to sales representatives.
Result: It helped the health care representatives to easily understand the incentive split and challenge them to improve more sales of the drugs
TXU Big Data
Situation: Reduce the customer attrition
Task: Built ML model to understand the reasons for attrition of customers
Action: Developed Logistic regression, decision tree models, preformed feature importance to reduce the features to reduce the processing time and to improve the performance of the model. Understanding the oil and gas industry to understand the features.
Result : Successfully was able to identify the areas affecting the churn in the electricity industry.

Education
Master of Science : Business Analytics And Information Systems, 2017
Bellevue University - Omaha, NE
J.D. : Electrical and Electronics Engineering
JNTU - Hyderabad,India, India
Certifications

SAS Programmer

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Resume Overview

Companies Worked For:

  • Ericsson
  • Oriental Trading Company
  • Marriott
  • Accenture

School Attended

  • Bellevue University
  • JNTU

Job Titles Held:

  • Data Scientist
  • Data Science Analyst
  • HR Data Analyst Intern
  • Senior Modeling Analyst

Degrees

  • Master of Science : Business Analytics And Information Systems , 2017
    J.D. : Electrical and Electronics Engineering

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