Nlp Engineer Data Scientist
Resume:
Sambit Pritam
******.***********@*****.***
Professional Data Scientist with 1.6 years of experience in Data Science and Analytics looking for Data Science/Artificial intelligence/Deep learning/Computer vision/NLP Engineer jobs only
Work Experience
Data Scientist at Tata Consultancy Services Jan 2017 -Present
Project Title: NID_CT Analysis Feb 2020 -Present
Role: Data Scientist (Microsoft Contact employee)
Tools & Frameworks: Jupyter Notebook, Google Colab, Azure Machine Learning Studio, Pycharm IDE, REST api, Flask Framework
Key Contributions
Involved in the entire data science project life cycle and actively involved in all the phases including data collection, data cleaning, developing models, validation, visualization with large data sets of structured.
Implemented Machine Learning, Deep Learning and Neural Networks algorithms using TensorFlow, Keras and designed Prediction Model using Data Mining Techniques with help of Python, and Libraries like NumPy, Matplotlib, Pandas, Scikit- learn.
Used Pandas, NumPy, Matplotlib, and Scikit-learn in Python for visualizing and developing various machine learning model.
Worked on imbalanced datasets and used the appropriate metrics while working on the imbalanced datasets.
Performed Data Cleaning, features scaling, features engineering using pandas and NumPy packages in python and build models using deep learning frameworks.
Generated various Predictive models by using different machine learning frameworks and tuned the best performance model using Microsoft Azure Machine Learning Studio.
Have worked on SQL, Power BI, Data Analytics and Statistics for better understanding of data.
Implemented Text Analytics and NLP modelling for Email Classification and Sentiment Analysis.
Key Achievements:
Reduced the blockage day count by 17 days.
Perfect analysis of SLA (helping the Customer to prepare for the future releases)
Project Title: Original Equipment Manufacturer October 2017 – Feb 2020
Role: Testing Engineer and Testing Analyst (Microsoft Contract employee)
Tools & Frameworks: Windows Testing Technology, SAP MST
Key Contributions
Functional testing in Digital Operating Center(DOC) which caters Global Business for Microsoft OEM operation.
Professional Summary
Experience in Machine Learning algorithms like Linear Regression, Logistic Regression, KNN algorithm, Support Vector Machine (SVM), Decision Tree, Ensemble Techniques like Random Forest, AdaBoost, XGBoost, K-Means Clustering.
Skilled in Minimizing the cost function-based algorithms like: Gradient Descent, Stochastic Gradient Descent, Mini-Batch Gradient descent.
Skilled in libraries like Numpy, Pandas, Matplotlib, Seaborn, Scikit Learn, Keras.
Data Visualization techniques with help of Matplotlib, Seaborn.
Skilled in Feature Engineering using Python: Feature Selection, Missing Value handling, Outlier’s handling, Data transformation, Describing the data using Python libraries like Numpy, Pandas and Matplotlib
In-depth knowledge of using Microsoft Azure Machine Learning Studio
Good knowledge of Deep Learning (DL) and hands-on with Neural Network Architecture, Loss Function, Cost Function, Optimizers, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), LSTM, and BERT.
Basic Understanding of Natural Language Processing (NLP) techniques like tokenization, stemming, lemmatization, Text Analysis, Matrix TFIDF and word2vec.
Basic understanding of Computer Vision Techniques like Image pre-processing, Image Segmentation, Object Detection, Object Recognition
Good Knowledge of linear algebra and dimensionality reduction algorithms like PCA
Hands on Experience in working with Dockers, Containers, GPU, and multiple GPU environment.
Experience of using Django and Flask Framework. Skills
Programming languages – Python
Python libraries – Jupyter Notebook, Numpy, Pandas, Matplotlib, Scikit-Learn, Seaborn, OpenCV, TensorFlow, Keras, Pytorch
Computational skills- Machine learning, Deep learning, OpenCV, NLP.
Machine Learning Algorithms: Linear Regression, logistic Regression, KNN, Decision Tree, Random Forest, SVM, PCA, Grid SearchCV,K Means Clustering, Pipelines.
Deep Learning: ANN, CNN, Architectures (VGG16, InceptionNet, MobileNet), Object detection and Localization algorithms like Sliding Window Detection, Yolo Algorithm.
Visualization Tools and Libraries: Basic understanding of Matplotlib and Seaborn
Others: Dockers, Azure Machine Learning Studio, Excel. Professional Certification and Courses
Advance Data science course with hands-on Google-Colab from Netzwerk Data Science Academy as ISO certified institute- year 2020
Certificate for attending the Online Workshop on Accelerated Data Science - February 2021 Achievements & Extra-Curricular
Attended workshops on “Microsoft Azure Virtual Training Day: AI Fundamentals”.
Attended workshop on “Power BI Training Program”.
Achieved award for cricket, football, badminton and carrom competition at school, college, and corporate level
Interpersonal Abilities: Problem Solving, Decision Making, Excellent Communication, Strong interpersonal skills, Team Player, Self-Starter. Leisure Interest
Playing football & Reading blogs
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