Sai Ratnam Peri

Sai Ratnam Peri

Data Engineer @ General Mills

About Sai Ratnam Peri

Sai Ratnam Peri is a Data Engineer at General Mills in Minnesota, United States, with a background in data science and engineering roles at phData, Inc. and the University of St. Thomas.

Company

Sai Ratnam Peri is currently employed at General Mills as a Data Engineer. Based in Minnesota, United States, General Mills is a global manufacturer and marketer of branded consumer foods.

Title

Sai Ratnam Peri holds the title of Data Engineer. His role primarily involves building data infrastructure, ensuring optimal extraction, transformation, and loading of data from diverse sources.

Education and Expertise

Sai Ratnam Peri earned a Master’s Degree in Data Sciences from the University of St. Thomas, where he studied from 2016 to 2018. He also holds a Bachelor’s Degree in Information Technology from Andhra University, completed between 2011 and 2015. His academic projects include Data Analysis & Predictive Modeling with Python, Machine Learning & Deep Learning, Big Data Architecture, Data Analytics & Visualization on Airline Delays Data Set, DevOps & Cloud Infrastructure, Data Warehousing, and Data Mining & Predictive Analytics.

Background

Before his current position at General Mills, Sai Ratnam Peri worked at phData, Inc. as a Data Engineer from 2019 to 2021, and as a Machine Learning Operations Engineer from 2018 to 2019. He has also served as an Analytics Consultant at the University of St. Thomas from 2016 to 2018, and interned at the University of Hyderabad in India in 2014.

Technical Skills and Proficiencies

Sai Ratnam Peri is proficient in various programming languages and tools, including R, Python, SQL, C, C++, Java, JSP, Servlets, HTML, XML, CSS, JavaScript, Hadoop, MapReduce, Hive, Pig, Impala, MongoDB, Neo4j, Spark, HBase, Sqoop, Oracle 10g, MYSQL, MSSQL Server, Eclipse, MATLAB, Tableau, SAS Enterprise Miner, PyCharm, GitHub, SAP HANA, R+H2O, and TensorFlow. He specializes in crafting algorithms for data mining and analysis and using data visualization tools to present insights to decision-makers.

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