Software Engineer Intern Resume

TECHNICAL SKILLS

Programming Languages: C, C++, Java, C#, Python, R, Android

Databases and Containers: MySQL, Oracle, PL/SQL, MongoDB, Cassandra, Docker

Web Development Languages and Frameworks: HTML, CSS, JavaScript, .NET, Entity Framework, Angular.js, Node.js, React, jQuery, JSON, REST, XML, AJAX, PHP, Bootstrap

Big Data Technologies: Apache Hadoop, Spark, Kafka, MapReduce, AWS, Zookeeper, Elastic Search, Logstash, Kibana

Platforms, Tools and IDE: Visual Studio, GitHub, Stash, Fork, Eclipse, JIRA, TeamCity, Octopus, Sentry, Databricks, Android Studio, Postman, NetBeans, Jupyter Notebook, PyCharm, RStudio

Data Science Libraries: NumPy, Pandas, scikit - learn, Matplotlib, tensorflow

Courses: Algorithms and Data Structures, Web Programming Languages, Database Design, Big Data, Machine Learning

PROFESSIONAL EXPERIENCE

Software Engineer Intern

Confidential

Responsibilities:

Developed and maintained existing web applications for healthcare in an agile environment. Worked on C#, .NET Core, MySQL, JavaScript, used Entity Framework to work with databases, developed database-driven user interfaces, unit testing with xUnit, CI/CD pipelines and JIRA. Also used Stash, Git, participated in scrum meetings, sprint planning and reviews.

Software Developer Intern

Confidential

Responsibilities:

Responsible for developing RESTful web API’s using Java Servlets and NoSQL Cassandra database, reusable UI components using Angular for Order Management Solution Platform running with Node Package Manager and Docker microservices.
Developed the product design, code following agile methodologies and testing using Jasmine, version control with GitHub.
Developed an android application for curb side pickup thereby efficiently using location-based services for faster pickup process.

Developer

Confidential

Responsibilities:

Developed a text mining based integrated system with user interface for bioinformatics specially prediction of diseases from gene that utilizes techniques like information retrieval, data collection, data cleaning and integration .
Used corpus of literature from PubMed database, implemented Decision Tree Classification algorithm for classification of gene names and predicting diseases. Data Preparation techniques implemented in R and used those results for classification in Python.

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