Research Analyst/ Data Scientist Resume Detroit, MI - Hire IT People

SUMMARY

Data analytics professional with eight years of clinicalresearch experience in delivering end to end data science projects.
Proficient in managing entire data science project life cycle and actively involved in the entire data science project life cycle including
Data acquisition (Primary and secondary data collection).
Power analysis, Hypothesis generation and testing, effect size.
Data cleaning, Data Imputation (Outlier detection using Chi Sq detection, Residual analysis, Multivariate Outlier detection.
Data Transformation.
Statistical modeling both linear and nonlinear ( Linear and Logistic regression, Naïve Bayes, Decision trees, Random forest, Neural networks, SVM, K means Clustering, MBA, KNN).
Dimensionality reduction using Principal Component Analysis (PCA) and Factor Analysis.
Testing and validation using ROC plot, K - fold cross validation, Confusion matrix and statistical significance testing, Data Visualization using R- gg2 plot package.
Experience in Exploratory Data Analysis, obtain insights from data then choose appropriate Machine Learning Algorithms (Classification, Regression, Association and Clustering).
Experience with SPSS, R (packages- Knitr, dplyr, data-table, SparkR), Python (sklearn, scipy, numpy, panda).
Experience in employing statistical models such as ANOVA, MANOVA, repeated- measure ANOVA.
Excellent written and verbal communication skills, preparing scripts for proper data access, manipulation and reporting functions with R.
Experience in writing journal articles and budget preparation for grant applications.

TECHNICAL SKILLS

Programming Languages: SPSS, SAS-Base, R, Python

Packages and tools: Pandas, NumPy, SciPy, Scikit-Learn, matplotlib, ggplot2, dplyr, data.table

Machine Learning: Linear regression, Logistic regression, Decision Trees, Support Vector Machines, Ensemble learning such as Random Forest, K-Nearest Neighbor, Unsupervised learning such as Market Basket Analysis and K-means clustering

Statistical Methods: ANOVA, MANOVA, Repeated Measure ANOVA, Linear regression, Logistic Regression, Survival Analysis, parametric and non-parametric tests

PROFESSIONAL EXPERIENCE

Confidential, Detroit, MI

Research Analyst/ Data Scientist

Responsibilities:

Participated in all phases of data collection, data cleaning, developing models, visualization, validation and presentation
Built a statistical regression model to diagnose sleep disordered breathing (Sleep Apnea) in aging population.
Responsible for performing Machine-Learning techniques such as regression/classification to predict the risk factors associated with sleep disordered breathing in obese, spinal cord injured patients, and aging population.
Performed Data Manipulation and Aggregation using dplyr R package, SPSS and Python libraries
Responsible in employing statistical methods to identify the impact of pharmacological treatments in patients with sleep apnea vs normal people using SPSS and R programs.
Extracted data of spinal cord injured patients from the Veterans Affair central portal of system using medical diagnostic code.
Formed a liaison between the Primary Investigators, sleep fellows and research assistants.
Presenting results in graphical format using gg2plot package, SIGMAPLOT in International conferences such as American Thoracic Society and Sleep.
Responsible for writing technical and statistical portion of the journal article released from the research group.

Environment: Python 2.x, R, HDFS, Hadoop 2.3, IBM SPSS, SQL Server 2012, Microsoft Excel, Matlab, Spark SQL, Pyspark.

Confidential, Detroit, MI

Intern in Maternal and Child Health

Responsibilities:

Performed data pre-processing and cleaning to prepare data sets for further statistical analysis including outlier detection and treatment, missing value treatment, variable transformation and other data manipulation technique using SPSS, R and SAS-Base
Involved in the process of manipulating historical data obtained from Medicare using SPSS and SAS-Base for model prediction analysis.
Utilized logistic regression analysis in R to identify risk factors for low birth weight babies
Performed cluster analysis to classify mothers into risk groups and associated factors involved in birthing low weigh babies
Accompanied Nurse Practioner in field visits and administered health questionnaire to expectant mothers.

Environment: IBM SPSS, Microsoft Excel, Microsoft Access, SAS-Base

Confidential, Detroit, MI

Research Assistant

Responsibilities:

Responsible for data collection, data entry, data pre-processing and cleaning data sets for further statistical analysis including missing value treatment, transformation techniques using R and SPSS
Involved in data visualization using R-gg2plot package and SPSS.
Involved in journal article searches and selecting appropriate articles for journal writing

Environment: IBM SPSS, Microsoft Excel, SAS-Base

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Research Analyst/ Data Scientist Resume

Detroit, MI

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