Teaching Assistant Resume

TECHNICAL SKILLS

Programming Languages: C, C++, Java, Python, R, Go language

Servers: Windows server 2003, Active Directory, Exchange Server

Database: SQL

Web Technologies: HTML, CSS, JavaScript

Tools: - S/W: Hadoop, Eclipse, Microsoft Office 2016, Weka

Operating Systems: Windows, Linux

Data Science Technologies: Numpy, Pandas, MatPlotLib, Scipy, Scikit-Learn, Preprocessing, Regression, Classification, Association rule learning, Reinforcement learning, Natural Language Processing, Predictive Modelling, Artificial Neural Networks, Convolutional Neural Networks, Keras, Tensorflow, Principal Component Analysis (PCA), Tableau, Time Series Analysis, Normal Distribution, Central Limit Theorem, Hypothesis Testing, T - Distribution, Z - Distribution.

PROFESSIONAL EXPERIENCE

Teaching Assistant

Confidential

Responsibilities:

Making the Questions, evaluating and grading the assignments.
Explain the concepts and clarify any doubts the students ask for.
Volunteer with the lab assistant in installing and maintaining the software required in the lab.
Coordinate with the professor to deal with the class schedules, relay information and teach a class if necessary.
Provide students with programming and software assistance.

Systems Engineer

Confidential

Responsibilities:

Understand the software architecture between the client and the customers.
Understand the Data that is coming into the Biztalk by fetching the details using SQL and make sure there is a smooth flow of Data until it goes out of Biztalk.
Look for any data specific errors or any network related errors in the system and resolve the issue.
Also make sure there is no duplication of the data.
Monitor different BizTalk servers (different Business Lines) for any issues and taking necessary actions when required.
Take care of multiple SQL jobs that are running and make sure they are completed periodically.
Deal with the tickets created, according to their priority and criticality by providing proper resolution.
Take care of different issues faced by the customers, clients and take them to closure.
If required, communicating with the client directly to resolve an issue.
Work closely with the Management team reporting the SLA compliance, daily & weekly metrics.
Co - ordinate with different teams for the smooth workflow.
Provide knowledge transfer to the new team members.

Systems Engineer

Confidential

Responsibilities:

Dataset considered is a high - dimensional gene expression data on Alzheimer's disease patients. Data Wrangling is done using numpy and Pandas. Also, Parsed and imputed this wrangled data.
Used supervised machine learning tecniques and statistical techniques to build three different classification systems and compared their effectiveness in predicting small set of test samples.
Achieved 87% accuracy using SVM classifier and k-clustering feature selection.

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