A self taught Data Scientist with 5 years of experience of working at product based companies. • Developed & presented a data science usecase for Cipla to World Economic Forum which bagged them Global lighthouse award. • 5 yrs experience of working in an agile model across various industries like Pharmaceuticals, FinTech, Networking, Career counseling. • My hyper eagerness towards applying data science or AI tech in my current field helped me in providing 2+ business use cases to previous organization which helped in sales and capacity planning using data science. • Developed design & lead a team for compensation project where a new architecture was introduced to split compensation among agents based on their involvement. • Received two best employee and two appreciation awards in one year of span. • Active contributor on Stack Exchange sites. • Language & Databases: C, Python, R, Java, Sql, Pl/Sql, Oracle, octave/matlab. • Machine learning Algorithms: Regression, ANN, K-Means, KNN, Naïve Bayes, SVM, PCA, Xgboost, clustering, Catboost. • NLP & Deep Learning: Stemming, Word2vec, Lstm, Lemmatization, Sentiment Analysis, TfIdf, Transfer learning, Object Detection, CNN, Computer vision, Sequence model, Bidirectional RNN, Word embedding. • Python libraries: Pandas, Opencv, Numpy, Xgboost, Lightgbm, Keras, Tensorflow, Sklearn, Matplotlib, Flask, NLTK etc. • Statistics and Probability: Confidence interval, T confidence, Hypothesis testing, Pvalues, Power , Bootstrapping, Binomial distribution, Bernoulli distribution, Normal distribution, Poisson distribution, Pmf, Pdf, Central limit theorem. • Big Data & Cloud: Hadoop, Map-reduce, Spark, Hive, Azure, databricks, data factory, Aws EC2, Sagemaker, S3. • Machine learning Mathematics: - Optimization using Hessian, Jacobian, Taylor series, Newton Raphson. - Reflection, rotation and transformation of matrices. - Page rank algorithm, Vectors, Eigen vectors and eigen values , Gram Schmidt process. • Winner of - HackWithInfy coding competition - Codevita coding competition • Certifications: Machine Learning by Stanford University, Linear Algebra by Imperial College London, Multivariate Calculus by Imperial College London, Statistical Inference by John Hopkins University • Interests: - Passionate about Artificial intelligence. - Like to do research oriented learning. - Inclined towards solving a big problem in healthcare industry using AI to help masses.