Data Analyst Intern Resume

TECHNICAL SKILLS

Python (Pandas, Numpy, Scikit - Learn, Gensim), SQL, Shell & Perl Scripting
Linear & Logistic Regression, Decision Tree, Bagging (Random Forest), Boosting (GBM, XGBoost),
PCA, SVM, Neural Networks, Deep Learning,
Apache Spark, Hadoop, Kafka
Sentiment Analysis (Nltk-Vader), Topic Modeling LDA, Word2Vector
Reporting, Proc SQL, Macros, Hypothesis Testing, Regression, Multivariate (Factor Analysis) Tableau (Tableau Public ), R ggplot2, Python (Matplotlib/Seaborn)
Microsoft SQL Server, MySQL, SQLite, Hive
Customer Analytics, Tableau, Data-Driven Decision Making-PwC by Coursera

PROFESSIONAL EXPERIENCE

Confidential

Data Analyst Intern

Responsibilities:

Built regression model to predict demographic sales using Python and Neural Network wif 92% Auc Score.
Used statistical techniques for hypothesis testing to validate data and interpretations.
Performed Factor Analysis to group multivariate resulting in set of two variables which increased the accuracy by 15%.

Confidential

Architecture Co-op

Responsibilities:

Implemented a regression model for expense analysis based on account type, business units and cost center.
Performed Contribution Analysis using Python throughout the SDLC for Global VM migration project.
Scraped the WebLogic Server live status using Perl scripts and displayed it on Tableau which saved downtime for applications.
Researched, documented and implemented architecture of “ITM” tool to streamline the monitoring process.

Confidential

Application Developer/Business Analyst

Responsibilities:

Developed a predictive model using Linear Regression to highlight KPI matrix to reduce customer churn for telecom client.
Transformed master data set using WTX to reduce error by 95% and loaded data to DB2.
Extracted data using SQL queries to build process optimization reports which resulted in saving 5 hours per day.
Translated business requirements into over 10 different tangible deliverables such as functional specifications, use cases, user stories, workflow/process diagram, data flow/data model diagrams(Visio).
Led daily Scrum meetings and acted as point of contact to clients by adhering the project progress as per SLA.
Data Transformation using LabelEncoder to perform machine learning algorithms on multiple categorical variables.
Performed Featured Engineering to reduce RMSE and built an TEMPeffective model using Linear Regression and Gradient Boosting.