Graduate Assistant Resume Example

Data Scientist highly motivated to explore the underlying story of data by applying and implementing the statistical knowledge and different programming languages. Love to prepare/pre-process data for a workable format for further analysis or storing by enjoying the painstaking part of data cleaning. Present the underlying story of data with visualization in a simple way that is informative and understandable for the people with even no knowledge of statistics or any programming skills after deep analysis of model fitting and comparing in case of both structured and unstructured data!

A temporal and spatial study of crime committed in Chicago

• Data cleaning, data manipulation, visualization, Imbalanced data
• PCA, K-Means Clustering, Extra Tree Classifier, Recursive Feature Selection, etc.
• Fitting Neural Network Model, Random Forest Model, Logistic Model, etc.
• Comparison using Confusion Matrix, ROC, AUC, etc.
• Checking Oversampling/Under Sampling, Predict the future Arrest Counts

Daily Crime Data in Chicago for the year 2012-2017

• Data cleaning, data manipulation, visualization, checking ACF, PACF, PCA, etc.
• Checking/removing Seasonality, Fitting SARIMA, Neural Network, Holt-Winters, etc. Models, compare models using RMSE, MAPE, Residual Analysis etc.
• Short term forecast, Long term forecast about the future crime

How does Sepal Width, Petal Length, Petal Width explain Sepal Length in different species of iris plant?

• Checking/Removing Outliers, Influential Observations, Residual Analysis, Sensitivity Analysis, Checking Collinearity
• Finding the best model that can explain the maximum variability by R-Squared, Adjusted RSquared

Factors that determine the Gasoline Consumption

• Checked the assumptions of multiple linear regression model and transformed the data for violation of any assumptions

A Study on Improving Livelihood of Rural Women Through Income Generating Activities in Bangladesh

• Hands-on experience in collecting primary data, designing the framework of the questionnaire and analyzing those data to deliver valid inferences for assessing the overall status of rural women

• Certificate for completing Machine Learning with Tree-Based Models in R from DataCamp
• Certificate for completing Unsupervised Learning in R from DataCamp
• Certificate for completing Fundamentals of Bayesian Data Analysis in R from DataCamp
• Certificate for completing Fundamentals of Visualization with Tableau from Coursera
• Certificate for completing SQL for Data Science from Coursera
• Graduate Record Examination (GRE): 316 [Verbal: 152 (55th Percentile), Quantitative Reasoning :164 (87th Percentile), Analytical Writing: 3.0 (17th Percentile)]