Data Analyst Resume

SUMMARY

Data Analyst with 4 years of research experience and 4+ years of academic experience.
SQL Developer with 4 years of professional experience and 4+ years of academic experience.
Proficient Working experience in designing database, writing SQL Queries, Stored Procedures, Functions, Indexed Views.
Professional in writing complex SQL queries on MySQL using a lot of subqueries, joins, aggregate functions, analytical functions, and temporary tables, etc.
Experience in predictive analytics procedures used in supervised learning (Classification, Regression, Decision Trees, Random Forest, SVM, Neural Networks), unsupervised learning (Clustering K - Means & PCA), and reinforcement learning.
Experience in implementing and consuming ML Algorithms and R-studio.
Expertise in performing data cleaning, transformation and ETL using Python.
Professional with solid Analytical skills for writing relational database solutions for businesses.
Good Understanding of GIT and analytical tools for data analysis.
A well-organized, goal-oriented, highly motivated and effective team player with excellent analytical, troubleshooting, and problem-solving skills.
Excellent Verbal and Written Communication skills and strong in Documentation.

TECHNICAL SKILLS

Languages: JAVA, JavaScript, C, Python, R

Web Technologies: HTML5, CSS3, JSON, PHP, Bootstrap, REST, GraphQL, Android, Spring MVC, Servlets, JSP.

Tools: R Studio, Jupiter, PyCharm, Crimson Hexagon, Microsoft Excel.

Databases/Cloud: MySQL, SQL Server, T- SQL, PL/SQL, SSIS, PostgreSQL, AWS (EMR, S3, EC2, RDS)

Hadoop Ecosystem: Hive, Pig, MapReduce.

Machine Learning: NumPy, Pandas, linear regression, polynomial regression, Logistic regression, KNN, Naïve Bayes

Visualization: Tableau, Matplotlib

PROFESSIONAL EXPERIENCE

Data Analyst

Confidential

Responsibilities:

Responsible for developing and Analyzing huge data using Crimson Hexagon and explored the tool for different languages and conducted launch events and seminars on crimson hexagon.
Our Analysis on the tool helped Graduate and Under-Graduate with their academic projects.
Worked as Research Assistant under 4 professors for data analytics projects and worked on sentiment analysis using Naïve Bayes Classification on news articles for huge amount of data sets and applied Machine Learning algorithms for the datasets.
Worked on time series analysis with R programming using R studio.
Worked on liwc sentiment analysis on diverse datasets like amazon review data sets and Reuters NLTK using python and NLP(natural Language Processing).

SQL Developer

Confidential

Responsibilities:

Actively designed and build RESTful Web Services that is consumed by Front End App and other components. Also, monitored and tuned database resources and activities for SQL Server databases.
Updated existing and created new reports using SQL Server Services and worked on stored procedures and PL/SQL.
Write clean and maintainable codes following OOPs concept and design patterns to ensure high availability, maintainability, and flexibility.
Perform code review, identify Code complexities, discuss and share comments, OOPs principles, and solutions to remove redundant, anti-patterns, tightly coupled codes.
Involved in writing testcases and performing unit testing for the application.
Work with business stakeholders, application developers, and production teams and across functional units to identify business needs and discuss solution options.
Created and updated database objects like Complex stored procedures, joins, tables, User Defined functions (UDF’s) for business logic.
Created views to facilitate easy user interface implementation, and triggers on them to facilitate consistent data entry into the database.
Experience in Creating and Updating Clustered and Non-Clustered Indexes to keep up the SQL Server Performance.
Transformed the data using different SSIS transformations like Aggregate, split, join, merge, derived column, Multicast, term extraction and data conversion of SQL Server Integration Services (SSIS).

Junior Data Engineer

Confidential

Responsibilities:

Worked on “Prediction of Diabetes Mellitus” where we collected the diabetes health dataset from caret library and preprocessed the dataset using R and applied Naïve Bayes and decision tree algorithm for classification and used specificity, sensitivity and accuracy to measure the classified effectiveness.
Trained the dataset using SVM (support vector Machine) algorithm which can be used for both classification and regression using the hyper line. Tested the dataset for all these algorithms to find the best algorithm for diabetes prediction .
Worked on Data Capture, Data Cleaning and analysis on health care data using python and R.
Worked in a team of 4 on an IOT based Deep Learning project using Raspberry-pi bot, enabled the movement of the bot and used video stream to train the neural network using COCO dataset to identify objects.