Computer Science Graduate passionate about leveraging data and computational power to build technological solutions at scale to solve challenging business and social problems. "More data beats clever algorithms, but better data beats more data" -- Peter Norving. I enjoy every step from gathering data and cleaning it to leveraging this data to build and deploy ML models. I am interested in not only finding hidden patterns and insights from the raw messy data but also love to use these insights to build predictive models that help the business make strategic decisions, improve customer experience and, increase revenue. Skills: ✔ Programming Languages: Python, R, Java, SQL, SCALA ✔ Web Technology/Database: HTML5, CSS3, JavaScript, MySQL, Oracle11g, MongoDB ✔ ML Libraries: NumPy, pandas, Matplotlib, Seaborn, Scikit-Learn, SciPy, NLTK, Gensim, Spark MLlib, Spark SQL ✔ Deep Learning frameworks: TensorFlow, Keras ✔ Big Data Technologies: Hadoop, MapReduce, Hive, Apache Spark, Apache Kafka, Elastic Search ✔ Cloud/Build Tools: AWS (EC2, S3, EMR, Glue, Lambda, CloudFormation), Google Cloud Platform, Docker, Kubernetes, Jenkins, RabbitMQ, CI/CD, Jenkins ✔ BI/ Analytic tools: Tableau, SAS ✔ Statistical Analysis: Regression Analysis, Hypothesis testing, A/B testing, ANOVA, Bayesian Analysis, Time Series Analysis, Survival Analysis ✔ Machine Learning Techniques: Decision Trees, kNN, Support Vector Machines, Logistic Regression, Ensemble Learning, Clustering, t-SNE, Principal Component Analysis, Association Rule Mining, Neural Nets, and Deep Learning ✔ Natural Language Processing: Text Preprocessing techniques, TF-IDF Vectorization, Text Rank, Multinomial Naïve Bayes, Sentiment Analysis, Topic Modelling, Text Classification ✔ Proficient in Algorithms & Data Structures, object-oriented design, problem-solving, complexity analysis and debugging ✔ Ability to work in an agile/scrum environment ✔ Descriptive Statistics and Inferential Statistics Please feel free to reach out at tejanaredla@gmail.com.