- Worked on the back-end python ETL scripts to optimize, change the data displayed on the front-end.-Worked with analyzing data of all employees across all divisions of the company and grouped them using python, excel.-Queried and Analyzed dynamo dB tables to make proposal changes to the users' accesses across the applications.-Moved data in to S3 and analyzed the Splunk reports to modify the python ETL scripts.

-Working on optimizing a home-grown python application to solve the delay issues in managing the cluster resources by profiling, refactoring the code.

-Worked on statistical analysis by processing of collected data and Data Visualization using Python packages like Pandas, Matplotlib, SciPy and NumPy.-Used data analysis to improve and personalize customer care.-Applied various ML algorithms to predict outcomes for various products offered by the company and to give inputs to the team on deciding how to improve the products.-Built the models on AWS platforms using Python and Spark for the model development and Dash by Plotly for… Show more -Worked on statistical analysis by processing of collected data and Data Visualization using Python packages like Pandas, Matplotlib, SciPy and NumPy.-Used data analysis to improve and personalize customer care.-Applied various ML algorithms to predict outcomes for various products offered by the company and to give inputs to the team on deciding how to improve the products.-Built the models on AWS platforms using Python and Spark for the model development and Dash by Plotly for visualizations.-Used Amazon Sage Maker to build, train and tune ML models, Amazon Athena to query S3 data with SQL expressions and Amazon Redshift Spectrum to analyze data that is stored across AWS data warehouses and S3 resources.-Used AWS Glue to load and prepare data.-Involved in requirement gathering and analysis phase of the project in documenting the business requirements by conducting workshops/meetings with various business users Show less

•Participated in all phases of data mining,data collection, data cleaning, developing models, validation, visualization and performed Gap analysis.•Extracted data from HDFS and prepared data for exploratory analysis using data munging•Built models using Statistical techniques like Bayesian HMM and Machine Learning classification models like XG Boost, SVM, and Random Forest.•Used pandas, NumPy, seaborn, SciPy, matplotlib, scikit-learn, NLTK in Python for developing various machine… Show more •Participated in all phases of data mining,data collection, data cleaning, developing models, validation, visualization and performed Gap analysis.•Extracted data from HDFS and prepared data for exploratory analysis using data munging•Built models using Statistical techniques like Bayesian HMM and Machine Learning classification models like XG Boost, SVM, and Random Forest.•Used pandas, NumPy, seaborn, SciPy, matplotlib, scikit-learn, NLTK in Python for developing various machine learning algorithms.•Worked on different data formats such as JSON, XML and performed machine learning algorithms in Python. Show less

•Worked with Machine learning algorithms like Linear Regressions (linear, logistic etc.) SVMs, Decision trees for classification of groups and analyzing most significant variables such as FTE, Waiting times of purchase orders and Capacities available and applied process improvement techniques.•Written MapReduce code to process and parsing the data from various sources and storing parsed data into HBase and Hive using HBase - Hive Integration.•Created SQL tables and developed advanced… Show more •Worked with Machine learning algorithms like Linear Regressions (linear, logistic etc.) SVMs, Decision trees for classification of groups and analyzing most significant variables such as FTE, Waiting times of purchase orders and Capacities available and applied process improvement techniques.•Written MapReduce code to process and parsing the data from various sources and storing parsed data into HBase and Hive using HBase - Hive Integration.•Created SQL tables and developed advanced queries using stored procedures and functions using SQL server management studio.•Used Pandas, NumPy, seaborn, SciPy, Matplotlib, Scikit-learn, NLTK in Python for developing various machine learning algorithms and utilized machine learning algorithms such as linear regression, multivariate regression, Naive Bayes, Random Forests, K-means, & KNN for data analysis Show less

• Extensively used Python's multiple data science packages like Pandas, NumPy, matplotlib, Seaborn, SciPy, Scikit-learn and NLTK.• Performed Exploratory Data Analysis, trying to find trends and clusters.• Built models using techniques like Regression, Tree based ensemble methods, Time Series forecasting, KNN, Clustering and Isolation Forest methods.