Data Social Media

Nikhil Dinesh Yajaman

*********@********.*** 972-***-**** www.linkedin.com/in/nikhil-dinesh-yajaman/ EDUCATION

University of Texas at Dallas, Richardson, Texas

Master of Science in Information Technology Management (Dean’s excellence scholarship), GPA 3.56/4 May 2020 Visvesvaraya Technological University, Mysore, Karnataka, India Bachelor of Engineering in Electronics and Instrumentation, GPA 8.45/10 April 2015 TECHNICAL SKILLS

Certifications Tableau, Python for Data science, R for Data science, Google analytics, Big data Programming Python, R, SAS

Databases RDBMS, SQL, Oracle, MySQL, Teradata, Snowflake Tools Tableau, MicroStrategy, Omniture, Google analytics,SAP HANA, MS Visual studio, Team Foundation Server, Dbeaver, Putty, WinSCP, DataStage, Jira, Advanced MS Excel (VLOOKUP, Pivot table, VBA, Macros, Data analysis),AWS(EC2,S3,Redshift,RDS)

Big data Hadoop, Hive, Map Reduce, Spark, Sqoop, Impala, Pig,Flume WORK EXPERIENCE

Data analyst intern, TCS through Insigma Inc, Houston, Texas, USA June 2019 – November 2019

• Analyzed customer data from retail stores and predicted customer buying pattern/trend using Market basket analysis.

• Built predictive models using MicroStrategy-R connection to forecast customer demand for leading clothing brand.

• Segmented customers using RFM analysis for targeted marketing campaign which resulted in increase in revenue by 10%.

• Performed data wrangling activities like cleaning, validating, using SQL and R to remove inconsistencies, missing values.

• Performed EDA using R, python understand the distribution of data and made data ready for reporting and analysis

• Facilitated sprint planning, daily scrum meetings, user story reviews with offshore team consists of 6 members.

• Migrated 20TB of data from Teradata to Snowflake data warehouse using python scripts from on-premise to AWS. Software Engineer, Aptean India, Bangalore, India August 2015 – June 2018

• Analyzed data using regression methods to predict the future maintenance of the machines and reduced costs by 20%.

• Automated SSAS cube processing by SSIS packages cutting the time to perform manual analysis by 384-man hrs. per year.

• Performed quantitative analysis using shop floor data using Tableau to increase visibility into quality of the production.

• Collected data from multiple resources into SQL and Implemented ETL using SSIS for checking data consistency, data completeness and accuracy dealt with over 800k records.

• Generated KPIs and created visual insights to suggest incident management strategy to higher management.

• Conducted root cause analysis of data issues, resolved recurring product issues, resulted in a decrease in issues by 15%. Skills: Statistical Data analysis, Data migration, Machine learning(Regression, Tree based models, Time series Analysis, K- means, SVM, PCA, xGBoost, NLP),AWS,Data visualization, ETL, Project Management ACADEMIC PROJECTS

Marketing predictive analysis using SAS SAS Linear, Logistic & Panel regression RFM analysis A/B testing Fall 2018

• Performed descriptive analysis to establish the current standing of the brand, built hypotheses about sales

• Performed factor analysis, Dummy variable regression, A/B testing, t-test, logistic regression to build logit model Human resource analytics using R Apriori Feature engineering Decision trees Classifiers Fall 2018

• Evaluated the attributes behind the attrition rate in a company using human resource data set and provided corrective strategies using the Apriori algorithm, decision trees and classifiers Sentiment analysis using Python NLP Sentiment analysis social media analysis Classifiers Spring 2019

• Provide options for device selection based on battery life and to determine data plan required Machine learning using Python Time series forecasting ARIMA K-means clustering Fall 2019

• Examined the factors affecting the sales in the online retail company and built forecasting models using e-commerce data. Database solution for a library Oracle SQL ERD Triggers Normalization Spring 2020

• Designed a database solution along with process diagrams using SQL, Oracle application express for a library. Big data analysis on Nationwide data of trucks Yarn MapReduce Sqoop Hive Impala Pig Spark flume Spring 2020

• Analyzed the nationwide commercial dataset to identify risk factors associated the trucks based on location and time.

Contact this candidate