Vivek Vardhan Rao Sirkonda

• Around 5 years of experience in in the entire SDLC life cycle as well as Data Engineer including Data Science, Data collection, Data Cleaning, Data Manipulation, Data Mining, Data Validation, Data Visualization, Analytics modeling and Designing algorithms. • Extensively worked on Python and R with various packages, MATLAB with various toolboxes. • Solid ability to write and optimize diverse SQL queries, and working knowledge of RDBMS and NoSQL DBMS. • Experience in working with Spark and different components in spark, pyspark, Python, Scala, Git, CI CD, Jenkins, Ansible, Cloud formation templates, SQL, NOSQL, Kafka, Hive, HBase, HDFS and Map reduce. • Good Knowledge in Amazon AWS concepts like EMR, S3, Lambda, Triggers, Glue, Step functions, Cloud watch events, Redshift, RDS, Athena, Kinesis firehose, data streams and EC2 web services which provides fast and efficient. • Strong experience in core Python, Scala, SQL, PL/SQL and Restful web services. • Encountered a wide range of data format including Structured data (Relational, Non-Relational data including Time series data, Spatial data, Graph data, etc.), Semi-structured data, Unstructured data. • Strong Knowledge in Bid Data environment and using tools like Hive and cloud-based data warehouse such as Teradata, Snowflake, Amazon Redshift, Amazon S3, Google Big query, Azure synapse Analytics. • Proficient in using different AI/ML platforms like Anaconda (Jupyter Notebook, Spyder), Google Colab, TensorFlow, Alteryx, Dataiku, RapidMiner, KNIME, Google Vertex AI & AutoML for data pre-processing and model prediction. • Hands-on experience with AWS cloud services (VPC, EC2, S3, RDS, Redshirt, Data Pipeline, EMR, Dynamo, Workspaces, RDS, SNS, SQS). • Worked on At Scale with Snowflake and created live connection between various teams and data. • Experienced in MLOps Concepts (Deploying, Monitoring, Maintenance) using Amazon Sage maker, Databricks, Google Cloud AI platform, Azure Data Bricks. • Good Experience in writing Map Reduce jobs using Java native code, Pig, Hive for business use cases. • Experience implementing NoSQL database technologies, including MongoDB, Cassandra, and HBase. • Highly skilled in statistical methodologies includes Experimental design and hypothesis test such as ANOVA test, T test, F test, Chi-square test, A/B test to prove the business assumption through data-driven analysis using Python and Excel. • Expertise in developing spark application using Spark-SQL and PySpark in Databricks for data extraction, transformation, and aggregation from multiple file formats for analysing & transforming the data to uncover insights into the customer usage patterns. • Familiarity with machine learning algorithm such as Linear Regression, Logistic Regression, Decision Tree, Random Forest, Naive Bayes, KNN, SVM, Neural Networks, CNN, RNN, K-means and Hierarchical clustering. • Hands on experience in building sophisticated models to address the business problems with machine learning models, Segmentation, Time series and other advanced analytical/statistical methodologies in Retail, Health care, Telecom, Insurance and financial services. • Performed data analysis and applied ML models in Various field includes medical diagnosis, product recommendation, fraud detection, Speech recognition, Image recognition and Stock market trading. • Experienced in ML model testing, Model deployment, model monitoring and model maintenance. • Excellent communication skills and understanding of System Development Life Cycle (SDLC) with Agile, Scrum and waterfall methodology. • Experienced with Integration Services (SSIS), Reporting Service (SSRS) and Analysis Services (SSAS). • Successfully working in fast-paced multitasking environment both independently and in collaborative team, a self-motivated enthusiastic learner.