Graduate Research Assistant Resume
SKILLS:
Data Science: Data Pre - processing, Cleaning Datasets, Data ad-hoc Analysis, Exploratory Dataset Analysis, Hypothesis Testing, Data Visualization, Creating Dashboards, Data Mining, Machine Learning, Supervised and Unsupervised Learning, SVM, NumPy, Pandas, ScikitLearn, Seaborn, matplotlib, ggplot, Python Libraries, Predictive Analytics, Statistical Analytics, Text Analytics, Natural Language Processing.
Tools: and IDE: GitHub, PyCharm, RabbitMQ, Docker, Kubernetes , Jira, SourceTree, Visual Studio IBM Watson Knowledge Studio, Microsoft ML Studio, Anaconda Distribution.
AI Tools: IBM Watson, Alexa Voice Service, AWS Lambda, Tableau, SAS
Programming Languages: Python, R, C#, Asp.net, JavaScript, HTML, CSS, Python Flask, Web Application Development.
Database: Database Design, MSSQL Server, SQL, MySQL, MongoDB, NoSQL
WORK EXPERIENCE:
Graduate Research Assistant
Confidential
Responsibilities:
- Design and Implementing AI Products from Scratch including Pipeline and Structure of Machine Learning Components.
- Building Machine Learning Models to analyze various Data from EMG and IMU Sensors generated by Noraxon.
- Leading a Team of 5 Undergrad Research Students in Various Projects.
Data Analyst
Confidential
Responsibilities:
- Build various Machine Learning Components like Model Metrics Evaluation, Data Analyzer, Model Executor, Model Ensemble. and build Docker images and Deploy it in Kubernetes Pods.
- Entity Extraction from Structured and Unstructured Data.
- Built a Product framework for unstructured data using .NET.
- Create Machine Learning Models using IBM Watson Knowledge Studio and Watson Explorer with accuracy of 98%.
- Development of Enterprise Application using JavaScript, .NET (4.5) and MSSQL Database for Route Management, Optimization, Order Dispatch, Delivery.