Engineer Data

Kush Patel

551-***-**** Dallas, TX ***********@*****.***

https://www.linkedin.com/in/PatelKushD https://github.com/kdpatel1810 EDUCATION

The University of Texas at Dallas, Dallas, USA

Master of Science, Business Analytics (Data Science) May 2021

GPA 3.86

Charotar University of Science and Technology, Changa, India Bachelor of Technology, Computer Engineering

May 2014

GPA 3.87

TECHNICAL SKILLS

Programming languages: Python, R, Shell Scripting

Tools/Software: Unix, Oracle DB, MongoDB, Tableau, Power BI, Talend (ETL Tool), MS Excel, Apache Hadoop, Docker, Kubernetes, GIT, JIRA, Confluence

Functional Skills: Statistical modeling, Applied Machine Learning Algorithms, Deep learning, NLP, Hadoop Ecosystem

– HDFS, Spark, Sqoop, Hive, Pig, Flume, Kafka, Impala, etc., Feature Engineering, Data Modeling & Wrangling, A/B Testing, Data Model Evaluation, Complexity Analysis, SDLC PROFESSIONAL EXPERIENCE

Sr. System Analyst, Sterlite Technologies Limited Python, RHEL, NoSQL, Hadoop March 2016 – July 2019

• Executed large scale multi-million-dollar digital transformation projects for telecom operator across the globe in Digital Engagement (BSS & OSS) and Analytics (Intelligent Data lake).

• Designed and architected a new Analytics Platform (Intelligent Data lake) to implement and evaluate machine learning models.

• Analyzed various large and complex structured and unstructured telecom data sets. i.e. CDRs, IPDRs, Customer tweets, social networking comments, IoT sensor data etc. and evaluated different machine learning models using cross-validation methods.

• Trained the supervised and unsupervised machine learning models with more than 3 months of customer data for various business cases i.e. customer experience, data monetizing, network optimization etc.

• Led the team for entire project lifecycle starting from design to customer training with average CSAT index - 4.5 out of 5. System Engineer, Sterlite Technologies Limited Python, JVM, RHEL, SQL, OpenStack, Docker January 2014 – March 2016

• Developed and implemented an optimized algorithm with efficiency to collect, process 1 billion call data records(CDRs) in a second and retrieve 10 million correlated IP data records and CDRs in IP Logger Management System (IPLMS).

• Implemented telecom mediation system on RHEL OpenStack (Cloud) and Docker to reduce the deployment time to half and ensured smooth rollout in a production environment with stringent customer deadline.

• Onsite requirement gathering, solution designing, implementation & integration of the solution, UAT with customer & business partners and conducted on-premise training and received excellent feedback certificate from the customers.

• Earned the CEO Excellence Award, Best Project Delivery Team and Best Project Execution Award. ACADEMIC PROJECTS

ID-less Entry System OpenCV, TensorFlow, Keras, CNN, RNN, scikit-learn

• Facial recognition and authentication to enter in premises by analyzing streaming video feed using deep learning algorithms. Study of Few Shot Learning and Implementation PyTorch, scikit-learn, CNN, RNN

• Prototypical Networks, Matching Networks, & Model-Agnostic Meta-Learning implemented on fashion Kaggle data set. Photo - Math Equation Solver PyTorch, scikit-learn, CNN, YOLO

• Detects math equations, labelling of linear and quadratic equations and provide the solution of detected math equations. Sentiment Analysis of Airline Tweets spaCy, NLTK, scikit-learn

• Analyzes tweet sentiments about airline review and tweets are classified into positive, negative and neutral sentiment. Unsupervised classification of Quora Questions NLTK, Non-negative Matrix Factorization, Latent Derelicht Analysis

• Discover topics and clustering keywords in same category using LDA and NMF on Quora questions. Agglomerative Hierarchical Clustering NumPy, pandas, Matplotlib

• Implement agglomerative hierarchical clustering – Dendrogram using centroid method and Euclidean distance from scratch. Econometric Analysis of Factors Affecting Aviation Fare Panel data, pandas, scikit-learn

• Fixed effect model developed to evaluate effects of variables (distance, number of passengers, service) on airfare. CERTIFICATION

Red Hat Certified Administrator & Red Hat Certified Engineer (ID: 150-124-832) October 2015 Neural Networks & Deep Learning, Natural Language Processing – Deeplearning.ai June 2020

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