Assistant Data Scientsist

SAI SRI NARNE

913-***-**** *****@****.****.*** linkedin.com/in/sai-sri-narne-b541aa140 https://github.com/SaiSriNarne EDUCATION

Master of sciences, Computer Science GPA: 3.68/4.0 University of Missouri- Kansas City, Missouri (Expected May 2020) Bachelor of Technology in Information Technology GPA: 9.22/10.0 RVR&JC College of Engineering, India April 2018

TECHNICAL SKILLS

Languages: JAVA, Python, SCALA, Hive, PHP, SQL, C++, C Web Design: HTML, CSS, JavaScript, XML, JSP, Servlets Databases: Oracle, MySql, Apache Cassandra

Framework and Tools: Spark, Hadoop, XAMPP

Version control systems: Git

WORK HISTORY

Graduate Teaching Assistant August 2019 - Present

University of Missouri-Kansas City

• Conducting tutorial sessions, facilitating classroom discussions and held weekly office hours

• Preparing quizzes, assignments and leading one lecture per week for each assigned course

• Grading of assignments, exams, and using assessment platforms of Canvas and Blackboard Excel and Access Tutor September 2019- present

UMKC Henry W. Bloch School of Management

• Helping students enhance their mastery of concepts and academic skills

• Maintaining accurate and complete records of student progress and development

• Assisting students in solving problems and clarifying concepts RESEARCH EXPERIENCE

Graduate Student, MS Thesis July 2019 - Present

University of Missouri-Kansas City

• Studying the classification techniques of text categorization

• Training a model on text features and class representatives on large text data PROJECTS

Chat Room Application- (Individual) March - May 2019

• Designed client server architecture that accepts TCP connection

• Implemented private and group chatting, users can also exchange multimedia files over chatting Environment: PyCharm (Python, SQLite, tkinter GUI) Visual Question Answering System on image dataset- (Co Lead) January - May 2019

• System is trained using pretrained VGG-16 pool5 feature model and RESNET block 4

• Question and answers were passed through LSTM. Achieved accuracy is of 65%

• Collaborated with a team of four in developing a knowledge base graph Environment: PyCharm (Python, Tensorflow)

Performance of Query Results on NFL based Tweets using Apache Spark – (Lead) August - December 2018

• Loaded twitter data into Spark Data frames and performed interactive spark SQL queries on data

• Used Tableau server to visualize the analysis

• Containerized entire project as Docker image

Environment: IntelliJ (Scala), Spark framework, Tableau Server, Docker

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