NEHA TAYADE

Bloomington, IN 812-***-**** ade1je@r.postjobfree.com linkedin.com/neha-tayade/ github.com/nehatayade18 EDUCATION

Indiana University, Master of Science in Data Science, Bloomington, IN, United States Expected May 2021 Coursework: Artificial Intelligence, Applied Machine Learning, Machine Learning for Signal Processing, Big Data, Deep Learning, Exploratory Data Analysis, Statistics, Internet of Things Ramrao Adik Institute of Technology, (B. E) in Electronics and Telecommunication, Mumbai, India Aug 2012 - Jun 2016 Coursework: Object Oriented Programming, Structured Programming Approach, Signals & Systems GPA: 7.8/10 WORK EXPERIENCE

Upped Events Inc., Data Science Intern, Philadelphia, USA Jun 2020 - Aug 2020

• Artificial Intelligence based chat bot: RNN RASA NLU RASA CORE Text semantics text relations TF-IDF Built a virtual agent based Chatbot using Recurrent Neural networks and NLP that acts as a feedback/dispute collector and helps customers for indoor navigation

• Prepared executive summaries and reports based on past events data to aid decision-making Tata Consultancy Services, Data Engineer- Business Intelligence & ERP, Mumbai, India Nov 2016 - Jul 2019

• Formed Oracle SQL/PL-SQL logics and designed solutions through engagement with senior management, external stakeholders and led a team of 5 junior members for full lifecycle development process

• Quantified business requirements and developed scripts for ETL jobs/workflows using BODS, DataStage and Informatica. Created BI reports/ERP dashboards using Crystal/WebI, Power BI and Tableau

• Delivered tasks in data analytics to organize relational databases (RDBMS) and designed data warehouses, data pipelines and architectures to facilitate frameworks for financial models use cases

• Overhauled issues by performing impact analysis / root-cause analysis on issues and optimized ETL jobs to save run-time by 5-30% TECHNICAL SKILLS

Programming Languages and Databases: Python, R, SQL, C, JavaScript, HTML, MySQL, MongoDB, PostgreSQL, Oracle, MS SQL Server Applications: Tableau, Power BI, RStudio, Informatica Power Center, AWS, Big Data Stack (Hadoop, Apache Spark), SAP BI Frameworks: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Keras, TensorFlow, Pytorch, Django, NLTK, TF-IDF, OpenCV, Spacy Machine Learning: KNN, AdaBoost, Random Forests, SVM, K-Means, Regression, Classification, XGBoost, Time Series, PCA, ICA, SVD Deep Learning: (Deep, Convolutional, Recurrent) Neural Networks, Generative Adversarial Networks, Attention Models, BERT PROJECTS

Twitter Sentiment Analysis and Entity Recognition Pytorch BERT Attention mask Bi-LSTM RNN Jul 2020

• Pre-processed over 1.5 million positive and negative tweets from Stanford dataset and build dataset (tokens, attention masks, pads)

• Used Transfer Learning to build Sentiment Classifier using the Transformers library by Hugging Face to classify with accuracy of 72%

• Trained an RNN for context analysis and recognized entities by using sequential Bi-directional LSTM for probability distributions over tags for tokens in sentences and train an RNN network with accuracy of 68% on test set Video Surveillance- Object Detection, Tracking and Captioning Python OpenCV YOLOv3 Google Colab Jun 2020

• Live video object labelling with confidence scores and motion tracking using pre-trained model to detect, localize and classify objects Facial Expression Recognition with Convolution Neural Network Python TensorFlow 2.x Keras Flask May 2020

• Emotion detection in real-time video stream with CNN model trained and deployed to web interface with Flask (accuracy 64%) Generation of Photo-Realistic facades from Architectural labels TF2.x Pix2Pix DCGAN CNN Feb 2020

• Reconstructed and synthesized input images using conditional adversarial network and optimized them with Deep CNN

• Predicted most profitable rides based on location, type and time of ride resulting in a revenue hike of 18% using algorithms Random Forest and XGBoost

• Compared trends during holiday season and anticipated revenue for future using ARIMAX model (time series forecasting)

• Marked popular pick-up/drop-off locations and predicted traffic at requested time using Quantile Linear Regression ACHIEVEMENTS AND CERTIFICATIONS

• Received Spot award for coding modules on Taxes, Account Statements & Invoices by Tata Consultancy Services

• Gold Batch for SQL programming

• Certifications: AWS, Deep Learning Specialization, NLP, TensorFlow 2.x, Computer Vision, Graph Theory Business Optimization for TLC- Green Taxi Revenue Rise and Traffic Prediction BigRed2 Dec 2019