Saikrishna Vanamala

Saikrishna Vanamala Chicago, IL |-| 312 - 684 – 4575 | linkedin.com/in/vsaikrishna93 | github.com/vsaikrishna93 Education Master of Science in Computer Science Expected May 2020 University of Illinois at Chicago (UIC), Chicago, IL • Relevant Coursework: Cloud Computing, Data Science and Machine Learning, OO Programming and Environments, Database Systems, Computer Algorithms, Computer Systems Security, Innovation and Entrepreneurship Bachelor of Engineering - Electronics and Telecommunication- Savitribai Phule Pune University (formerly University of Pune) • Honors: University Rank 7th in the Sophomore Year. • Coursework: Data Structures, Algorithms, Systems Programming, Operating systems, Computer Networks, AI Professional Work Experience Associate Data Engineer Intern June 2019 – August 2019 Publicis Spine – Publicis Groupe • As part of PeopleCloud solutions team, was responsible for design and development of a Data infrastructure platform – an amalgamation of public and private cloud (AWS, GCP, Azure and On -premise). • This platform provided the Data Scientists a one stop platform to perform Data Analysis for multiple clients of Publicis. Data Engineer - Graduate Assistant January 2019 – Present UIC – School of Public Health (SPH) • Data Integration using MS SSIS, SSRS, Power BI, Web development, Database administration. Systems Engineer – Data and Analytics August 2015 – July 2018 (3 years) Infosys Ltd. • Served a Financial Services client - Charles Schwab Co. as part of their Global Data Technology (GDT) team. • Working Domain: Design and maintenance of optimal Data pipeline architecture for batch scheduling automation platform - ETL/ELT, Map/Reduce using Hadoop, Spark with HDFS, Data-warehouse modelling, Data Quality, Data Governance, Master Data Management, Disaster Recovery, visualization - interactive dashboard and reports Technical Skills and Abilities • • • • • Proficiency in Programming: Industry level - Java, Python, Scala, SQL, Golang, C++, C. Academic - C#, Matlab Relational DBs: Teradata, MS SQL Server, MySQL, Oracle Distributed DBs/Filesystem: HDFS, HBase, MongoDB, S3 Software Frameworks: Hadoop - Map/Reduce, Apache Spark, REST API - SpringBoot MVC and Jersey, Java RMI, gRPC Tools/IDEs: AWS (EMR, EC2, S3, Athena, Cloud9, Redshift, Kinesis), GCP (BigQuery, DataStudio, ML-Engine), Informatica Power Center, MS - SSIS & SSRS, IntelliJ IDEA, Jupyter, Eclipse, Docker, Visual Studio, sbt, maven, git ML Algorithms: Classification (Decision Trees, SVM), Regression (Linear, Ridge), Ensemble Learning, Clustering (K-Means) Major Projects Undertaken • • • • Design and Implementation of Disaster Recovery Plan for Enterprise Data-warehouse - [at Infosys Ltd.] § Disaster recovery mechanism ensured backup of data in case of system failure or damage. A backup storage was designed for a Teradata Warehouse on a Hadoop cluster using Teradata Connector for Hadoop (TDCH). § The direct access of data from the Hadoop Cluster was facilitated using Hive SQL and custom Map/Reduce jobs. End to End Financial Data Pipeline design and Infrastructure Maintenance - [at Infosys Ltd.] § Daily transactional data was stored in multiple forms as per the individual application design. These sources were downstreamed into a central Enterprise Data Warehouse using a complex Batch scheduling automation platform. § Designed and Developed ETL - Informatica Workflows to use efficient push down optimization and decrease latency. § Automated Data Integration using Teradata BTEQ scripts by combining functionality of FastLoad, MultiLoad and TPump. Implementation of Page Rank Algorithm for a large XML dataset on Spark Cluster – [Academic at UIC] § Designed and implemented page rank algorithm to rank UIC CS faculty authors based on their co-authorships on publications and also the venue of publications using Spark framework. § Deployed the spark application (assembled using sbt) on Standalone local cluster and also on AWS - EMR Spark Cluster using YARN resource manager and HDFS as distributed storage system. Design of a Prediction model to predict Effects of Unhealthy Behaviors on Chronic Diseases – [Academic at UIC] § Developed, visualized and designed a Prediction model to predict the effects of unhealthy behaviors such as Low Physical Activity, Smoking and Lack of Sleep on two Chronic Diseases – Obesity and Cancer. Built a Linear model using Linear Regression and Ridge Regression and improved prediction accuracy to 0.919 using Random forest regressor.