Data Analysis

Golnaz Toloui

************@*****.*** +* (***) *** - 0725 https://www.linkedin.com/in/golnaztoloui Summary

Passionate Data Analyst and Consultant with advanced educational background in Economics, Machine Learning, Statistics and Data Mining . Enthusiastic about explaining the data science to non-technical business audience. Self-driven, quick learner and energetic team player with excellent problem solving skills with domain experience in Finance and Health Care ( with ability to relocate ) . Work Experience

● CVS Health, N orthbrook, IL ( March 2017 - Current) Analytics Consultant Enterprise Innovation Department Applying the translation of needs of the business clients and stockholders regarding the specialty therapies into analytic questions, using SAS and Teradata to access big data and analyze the underlying concepts and developing Tableau dashboards to visualize the extracted findings . Generating and updating as appropriate accurate reports for review by the Specialty Operations Management and Profit & Loss team . Extracting, measuring, tracking and recommending potential opportunities to improve the performance of the business based on the Therapies like Oncology, Autoimmune, Drugs (Generics or Brands), Patient’s demographic characteristics and Conducting rigorous analysis of Pharmacy Claims, Medical Claims based on the needs of the existing business partners . Maintaining Pharmacy Benefit Management analytics and applying the trend analysis to present clinical and financial opportunities to launch new programs .

Applying technical analysis on Medicare requests using different healthcare metrics .and measurements like Discontinuation Ratio, Medication Possession Ratio, Patient's Adherence and more.

● DePaul University, C hicago, IL ( September 2016 - March 2017) Graduate Assistant Tutor College of Computer and Digital Media Mentored Graduate and Undergraduate students with statistics, database and data mining concepts and related softwares .

● DePaul University , C hicago IL ( January 2016 - June 2016) Graduate Assistant CMAP Research Project, Institute of Housing Studies Applied data munging, cleaning, explorator y data analy sis, using machine learning algorithms for developing predictive models and created visualizations for making decisions based on the findings . Performed unsupervised learning (clustering) both on 2014 and attributes which were changed from 2011 to 2013 to find patterns in characteristics of Chicago Greater Area housing trends during the past years . Applied outlier detection for find weak members of each clusters and deal with them appropriately.

● Kerman Carton Co., D ubai, United States of Emirates (August 2010 - August 2014) Financial Analyst

Performed technical analysis to determine present and future financial performance, model building and predictions based on the existing data regarding the company’s business and ma intained up-to-date knowledge on investing practices. Performed economic research and studies in the areas of Rates of Return, Depreciation, Working Capital Requirements and Investment Opportunities.

Developed and managed SQL queries of r elational databases t o support the audit function and wo rked closely with all levels of business users to clearly define reporting requirements in support of strategic decision making.

● Iran-Mehr Language Institute, T ehran, Iran ( September 2012 - August 2014) Volunteer English Instructor / c oncentration in IELTS ( International English Language Testing System) Education

DePaul University, C hicago, IL ( March 2015 - Expected Graduation June 2017) Master of Science in Predictive Analytics (Concentration in Computational Method - GPA 3.9/4) Projects:

● Animal Shelter Outcome, Kaggle competition: A pplied various supervised and unsupervised learning algorithm to predict the outcome of animal shelter using Python’s different libraries and RStudio.

● Time Series Analysis of USD/EUR Exchange Rate: Applied ARIMA models, Seasonal ARIMA, Prediction and back-testing to predict the exchange rate . implemented using RStudio.

● Time Series Analysis of Unemployment Rate: Applied Heteroscedastic GARCH and EGARCH models and forecasting the unemployment for the USA . Implemented using RStudio.

● Automobile Dataset UCI: Applied multiple stages of Regression Analysis like Data Cleansing, Data Split-up, Model Building, Model Adequacy, Model Assumptions and Model Validation to propose a final model which can predict the car’s price using the most influential predictors. Also collected the recent dataset as the validation set to text the performance of the final model . Implemented using RStudio and SAS.

● Chicago Housing Data: A pplied Canonical Correlation Analysis and Principal Component Analysis to analyze and extract relations between house values and household characteristics based on the demographic features of the households and the living spaces and diverse vicinities in Chicago,, using RStudio.

● Customer Segmentation: Applied Gaussian mixture Models and Bayesian Network models to extract the behaviours of the customer, association between different items based on their expenditure behaviour and segmenting the customers into groups with similar demographics or buying patterns for target marketing campaigns, using RStudio.

● Gender Recognition by Voice: A pplied Support Vector Machine as supervised machine learning approach to classify the gender of the voice based on the human’s vocal characteristics using various kernels . implemented in RStudio

● Chicago Taxi Data: Visualization of the Chicago’s Taxi dataset using Tableau to extract the meaningful insight from individual

● Taxi’s demographic and characteristics features in Chicago, IL for year 2016 . A zad University of Tehran, T ehran, Iran (July 2006 - August 2010) B achelors of Science in Theoretical Economics G PA 3.3 / 4 Relevant Courses

Tools and Techniques for Analysis Introduction to Programming using Python Knowledge Discovery Technique Mining Big Data

Database for Analytics Programming Data Mining Applications Advanced Data Analysis

Neural Networks and Deep Learning

Time Series Analysis Forecasting

Advanced Data Mining

Scripting for Data Analytics

Data Analysis and Regression

Intelligent Information Retrieval

Data Visualization

Stochastic and Statistics for Managers

Management Law

Skill and Proficiency

Supervised and Unsupervised Machine Learning: Classification, Regression, Clustering, Decision trees, Support Vector Machines, Kernel Principal Component Analysis, Bayesian Networks Markov Models, Gaussian Mixture Models, Random Forest Ensembles of Classifiers, Bagging, Boosting, Association Rule Mining, Recommender Systems, Information and Document Retrieval, Text Categorization, Deep Learning, Artificial Neural Networks and Artificial Intelligence .

Statistical Methods: R egression, Significance Testing, Hypothesis Testing and confidence intervals, Bayesians Statistics, Principal Component Analysis and Dimensionality Reduction Techniques, Linear Discriminant Analysis, Canonical Correlation and Factor Analysis . Languages: P ython (Scikit-learn, Pandas, Numpy, Scipy, Tensor Flow, Lasagne, Theano), R, MATLAB, OCTAVE, B ase SAS, Macros, Proc SQL, SAS EG , linux

Databases: O racle SQL Developer, MS Access, Teradata, DB2, Hadoop, HDFS, MapReduce, Hive, Pig, AWS Amazon Cloud computing, NoSQL, Spark, Hadoop Streaming

Visualization Tools: T ableau Desktop, ggplot2, sgplot S oftwares: S PSS,Weka, Excel

Language Fluency: E nglish, Spanish, Farsi, Azari

Awards: D ePaul University Graduate Assistantship Scholarship for the 15/16 Academic year .

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