Python Developer
CurrentExtracted data from the database using SAS/Access, SAS SQL procedures, and created SAS datasets.Transformed database reporting needs into powerful SQL queries to extract and compile data into meaningful reports.Proficient in machine learning modeling, regression, clustering, and classification using Python and R.Experienced in building servers using AWS, including importing necessary volumes, launching EC2 instances, creating security groups, auto-scaling, load balancers, and configuring Route 53 and SNS.Implemented a Continuous Delivery framework using Jenkins, Jfrog, Maven, and Nexus in a Linux Environment, deploying into AWS using the Jenkins AWS Code Deploy plug-in.Added support for Amazon AWS S3 and RDS to host static/media files and the database in the Amazon Cloud, with proficiency in deploying projects using Jenkins.Wrote Python scripts to parse JSON documents and load data into the database.Utilized Spark and Spark SQL for data integrations and manipulations, working on a POC for creating a Docker image on Azure to run the model.Used Pandas as an API to organize data as time series and tabular formats for manipulation and retrieval.Worked on AWS CLI Auto Scaling and Cloud Watch Monitoring creation and update.Experienced in machine learning algorithms such as Linear Regression, Logistic Regression, Naive Bayes, Decision Trees, K-Means Clustering, and Association Rules.Worked with time series data and performed various statistical and machine learning algorithms such as LMS, regression, filtering, correlation, and neural networks.Environment: MySQL, MSSQL, Python 3.x, Git, JSON, Spark, Docker, Azure, SAS/Access, SAS SQL, AWS, Machine learning, artificial intelligence, Python, R, Chef Automation, EBS, S3, VPC, LDAP, VPN, RDS, SES, ELB, Autoscaling, CloudFront, CloudFormation, Elastic beanstalk, Cloudwatch, SNS, Route 53, LDAP, VPN, AWS S3, RDS, Git, JSON, IAM, CLI, API.