Yesmine Bellalah

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Data analysisData science Statistics

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General informations

Name : Yesmine Bellalah

Sexe : woman

Birth date : 12-Mar-1994

Nationality : Tunisia

Price per day : Premium members only

Contact

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Skills

inferential statistics

Business Management

CSS

Correspondence analysis

Data analysis

HTML

Macro-economy

Maple

Micro-economy

Microsoft Office

Pascal

PowerAMC

Principal component analysis

SAS

Tableau software

VBA

Degrees

Mathematics and Physics

School : IPEIT : Preparatory institute for studies of engineer of Tunis

Year : 2013-2015

Experiences

Insertion internship : "Recent Methods from Statistics and Machine Learning for Credit Scoring" in the Bank of Tunisia (BT)

Start date : 01-Jun-2016

End date : 30-Jun-2016

About : Data mining is a critical step in knowledge discovery involving theories, methodologies and tools for revealing patterns in data. It is important to understand the rationale behind the methods so that tools and methods have appropriate fit with the data and the objective of pattern recognition. There may be several options for tools available for a data set. When a bank receives a loan application, based on the applicant’s profile the bank has to make a decision regarding whether to go ahead with the loan approval or not. Two types of risks are associated with the bank’s decision – If the applicant is a good credit risk, i.e. is likely to repay the loan, then not approving the loan to the person results in a loss of business to the bank If the applicant is a bad credit risk, i.e. is not likely to repay the loan, then approving the loan to the person results in a financial loss to the bank To minimize loss from the bank’s perspective, the bank needs a decision rule regarding who to give approval of the loan and who not to. An applicant’s demographic and socio-economic profiles are considered by loan managers before a decision is taken regarding his/her loan application. MISSION : - Review the predictor variables and guess from their definition at what their role might be in a credit decision ( Exploratory data analysis ) - Develop classification models using the following techniques :Logistic Regression (LR) - Report the confusion matrix and the ROC chart Tool: R

Tunisian Political Attitudes Survey (TPAS)

Start date : 01-Mar-2016

End date : 30-Mar-2016

About : This project was conducted by a PhD candidate in the Department of Government at the University of Texas at Austin in partnership with academics at ESSAI. The 1,800-respondent survey drew both on an Internet convenience sample through Facebook advertisements and on face-to-face surveys. I was the enumerator who oversaw the face-to-face recruitment efforts for the Nabeul governorate. I conducted surveys in this region which was underrepresented in the Internet convenience sample.