Data Analyst
- HR / Recruitment
-
- Work experience involving the qualitative/quantitative data analysis to solve the problem
- Extensive knowledge of using statistical modeling techniques, such as univariate and multivariate regression, Hypothesis Testing, Parametric/Non-parametric methods, Analysis of variance, Principal component Analysis.
- Knowledge in using the Supervised & Unsupervised Algorithm’s and Techniques Linear, logistic Regression, SVM, Random Forest, KNN, Navie-bayes, K-means.
- Experience and Knowledge of using common analytics tools R, Python, Excel, SPSS, Gretl, Advanced Excel.
- Experience with data visualization tools, such as Tableau Desktop, Power BI
Skills:
- Programming/Scripting Language: R, VBA, Python
- Database Query Language: Basics of C, C++, SQL
- Visualization/Reporting Tools: Tableau, RStudio, Power BI, Excel, SPSS, Gretl.
- Knowledge: Descriptive and Inferential Statistics, Machine
Learning, Predictive Modeling, Datamining Techniques
And other statistical techeniques.
Academia:
- M.sc (statistics) from Pondicherry Central University from Pondicherry (2012-2014).
- B.sc (MSCS) from Andhra Loyola College (2009-2012).
Professional Summary
Currently Working as Senior Data Analyst in Sunmeister Energy Pvt.Ltd from June-2018 to Current
Have Two years of Working Experience as Jr. Data Scientist in Adsiduous Media Private Limited (Digital Marketing) Aug-2016 to May-2018
Have 1.6 Years of Teaching Experience as Faculty in Statistics (2014-2016)
Projects:
Project at P.G level
Title: Financial Forensics and Statistical Investigation through Data Envelopment Analysis with Reference to Indian Co-operative Banks
Role: Involving data collection and analyzing the data, Responsible position (Team Lead)
Analysis performed: Descriptive statistics, Correlation Analysis, Operation Research Methods & Predictive Modeling
Tools: MS-Excel, DEAP (Data Envelopment Analysis Program) and SPSS
Overview: In this project, mainly, we took into consideration of cooperative banks of five years data from 2007-2012, we checked their performances by taking the help of input and output variables by computing technical efficiencies by using the Operation Research (OR) software DEAP (Data Envelopment Analysis program). We concluded that the “xxxxxx” is poor in its performance due to the output variable net fixed assets and we found the correlation with this variable with the other input/output variables and suggested “xxxxxx” to concentrate on those variables which are related with net fixed assets so that they can improve their performance for the forthcoming years.
Project at Office level: (Digital Marketing)
Predictive Modeling, Classification Techniques
- Predictive Modeling is used to Predict the Revenues, Impressions and other elements related to business from Advertisers, and Classification techniques to decide the extension of Relation with effective Publishers or Advertisers.
- Optimizing the Available Volume/Inventory.
- Handling the market places like LKQD, AOL, STREAMRAIL etc.
- Regulating the invalid Traffic to increase the revenue and advertisers Relationship.
Description:
- LKQD, AOL, STREAMRAIL are the marketplaces (where the exchange of volume takes place or Platforms where Business Runs)
- Generate the Daily Weekly and Monthly reports from Platforms.
- Analyze the data and perform Descriptive statistics analysis.
- Making Best use of Available Volume.
Environment: Excel, R, Tableau (visualization of basic elements),Power BI
Additional Achievements:
- Achieved 2 prize in International Conference Competition organized by ISPS during the year 2014 at P.G level
- Participated certificate for attending a workshop on Indian population censuses.
- Secured 6 rank in Ph.D. Entrance for Pondicherry Central University
I hereby declare that all the above details furnished by here are correct to the best of my knowledge and belief