A curiosity-driven data scientist, eager to leverage machine learning and data analytics to extract meaningful insights, make informed decisions and solve challenging business problems. I ensure to contribute with my knowledge, logical thinking and analytical skills towards the consistent growth and development of the organization, and enhance my experience through continuous learning and teamwork. Good in statistical & quantitative analysis of structured & unstructured data. Data driven decision making. Proficient in Machine Learning, Deep Learning and Natural Language Processing using R &Python. Possess clear understanding of how supervised, unsupervised machine learning & deep learning algorithm works. Working knowledge of Machine Learning algorithms like Regression, SVM, Decision trees - Ensemble Techniques - Random Forest, Adaboost, Xgboost. Working knowledge of Deep Learning neural networks- ANN, CNN, RNN. Good exposure to data mining techniques like clustering, market basket analysis and PCA. Data Visualization in Tableau making dashboards. Working knowledge of Tools for model deployment: Rshiny, Flask, Heroku. Tool for deployment: Heroku platform. Good interpersonal, presentation and team skills. SKILLS • Statistics – Various hypothesis testing, estimation, probability theory, time-series analysis, statistical modeling. • Machine Learning – Algorithms for Regression (Linear, Logistic), Classification (Decision Trees, Random forest, XGBoost,SVM, Naïve Bayes, k-NN),PCA, Clustering(k-means, Hierarchical). • R - Implemented ML Algorithms, used packages like dplyr,glmnet, ggplot, caret,boruta, missForest, mice, dummies •Python - ML Algorithms, using packages like Numpy, Pandas, SciPy, Scikit-Learn, Statsmodels, Matplotlib, Seaborn • Natural Language Processing – Text Processing, Web Scrapping, Sentiment Analysis, Regular Expressions, NLTK • Deep Learning – Neural Networks, RNNs, CNNs, LSTMs; tensorflow, keras. • SQL - Performing Basic Queries, Sub-queries, Joins, Aggregation, Statistical Functions. •Tableau / Power BI / Qliksense – Data Visualization, Business Intelligence, Forecasts, Tables, Charts, Dashboards •Big Data – Basic knowledge of Hadoop, Map Reduce and Spark, along with all the other tools of the eco-system.