Name : Pavithra S M

Father’s Name : Mariswamy

Date Of Birth : 10 Feb 1993

Gender : Female

Nationality : Indian

Language Known : English,Kannada,

Telugu.

Professional Summary

Data science enthusiast with complex algorithmic and statistical mindset. A highly skilled, competent, and diligent individual is seeking an opportunity to establish a career as a Data Scientist. Strong willingness to exhibit my proficiency in Analytical tools, Statistical and Computing Methodologies in the professional environment. Bringing specialized expertise in designing data input structure and statistical models. Possess mastery in using data analytical tools to enhance management business strategy for profitability.

Pavithra S M

Email Id: ada2tj@r.postjobfree.com

Mobile: +91-974*******

Bangalore, India

Key Competency Areas

Business Analytics

Statistical Analytics

Exploratory Data Analysis

Predictive Modelling

Python

Microsoft Office Tools

Analytics Experience

Project 1:-

Industry: Banking

Objective:- Predicting Bank Customer Churn

Customer Segmentation and Profiling

1.Performed data cleaning, data integration and data preparation to enable further analysis.

2.Developed basic customer profiling to enable the understanding of the data and the business aspects of the project

3.Assisted the Domain Consultant and Senior Statistical Consultants in model development.

4.Develop predictive models for Bank Customer Churn, Applied supervised machine learning techniques like Logistic Regression, Decision trees, etc. To develop predictive models using python.

5.Evaluated models on parameters like Confusion Matrix, ROC Curves, KS Statistics, etc. And selected best model based on performance on training, testing and validation data sets.

Project 2:-

Industry: Banking

Objective:- To Analyze and Predict if the client will subscribe to term deposit.

1. Performed data cleaning, data integration and data preparation to enable further analysis

2.Developed the model for Term Deposit using Logistic regression, and Decision Tree using python.

3.Scoring the model based on the selected model.

4.Performing Long term and short term behavior.

5.Behavior of the customer based on the transactions.

6.Creating information maps based on the requirement (which will be input for campaign)

Education

MCA (2013 – 2016) – 71%

Bangalore University.

Bangalore, India

BCA (2010 – 2013) – 74%

G.T Institute of advanced studies.

Bangalore, India

Technical Skills

Software s:

Python,

SQL

Microsoft Office Tools.

Statistical Techniques:

Descriptive Statistics

Testing of Hypothesis(t-test,

z-test, Chi Square, ANOVA)

Classification / Regression

Linear Regression

Logistic Regression

Decision Trees

Cluster Analysis

Time Series & Forecasting.

Previous Work Experiencece

Previous Work Experiencece

Work Experience

KSBL (From Nov 2018 To Apr 2019)

Business Development Executive

IIFL (From July 2017 to Oct 2018)

Relationship Manager

Project 3:-

Objective:- Predicting Employee churn or Employee attrition.

1.Performed data cleaning, data integration and data preparation to enable further analysis

2.performed statistical analysis solutions like(univariant analysis,

bivariant analysis, logistic regression and decision tree).

3.segmented the employee performance and job involvement into high value, low value, moderate value segments and developed.

4.Developed basic employee profiling to enable the understanding of the data and company aspects of the project.

5.Developed predictive model for Employee Attrition using logistic regression model and decision tree using python.

6.Evaluated models on parameters like confusion matrix, roc curve, KS statistics.

7.Selected the best model based on the performance of training, testing

and validation of dataset.

Project 4:-

Industry: Banking

Objective:- To predict how likely a credit card request will approve.

1.Performed data cleaning, data integration and data preparation to enable further analysis

2.Performed Category segregation of the credit card data based on the customer transaction data

3.Performing Long term and short term behavior

4.Behavior of the customer based on the Credit and Debit transactions

5.Creating information maps based on the requirement (which will be

input for campaign).

6.Developed the model for Credit Card using Logistic regression, and Decision Tree using python.

7.Selected the best model based on the performance of training, testing

and validation of dataset.

Declaration :-

I hereby, declare that all the above details are true to the best of my knowledge.

I shall be solely responsible for any kind of discrepancy found in them.

Date:

Place: Bangalore Pavithra S.M

Personal Details

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