About

Snigdha Kakkar is a highly skilled Machine Learning Developer with over 4.86 years of experience in software design, development practices, machine learning, user acceptance testing, and Big Data. She is currently pursuing a Masters of Engineering (ECE) with specialization in Artificial Intelligence and Machine Learning at the University of Waterloo. Snigdha is also an MBA graduate from XLRI, with a specialization in Business Administration and Management. Snigdha has a strong technical skillset, with expertise in programming languages such as Java, Python, C, C++, and MATLAB. She is also proficient in data science tools like Python, R, Scikit-Learn, Tensorflow, and Keras, as well as BI and analytics tools like Data Engineering, R, VBA MS Excel, and PL/SQL. She is skilled in statistical analysis using R and has experience in Cloud computing using GCP, Docker, and Kubernetes. With experience in data engineering tools like Google Data Cloud, Hadoop, Hive, Spark, IBM SPSS, Java, Python, SQL Queries, and Power Query, Snigdha is also proficient in data visualization tools like Microsoft Power BI and Tableau. She is well-versed in Microsoft Office (MS Word, MS Excel, and MS PowerPoint), MS Visio, MS Access, and MS Project. Snigdha is also experienced in GitHub and Git, as well as object-oriented methodologies, SAAS, SDLC, Agile methodologies, and UML diagramming. Snigdha has worked as a Graduate Research Assistant at Ryerson University, where she worked on machine learning and deep learning-based projects. She has also worked as a Technical Support Advisor at Transcom. Currently, she is working as a Machine Learning Developer at IBM. Snigdha has a strong educational background, with a Master of Engineering (MEng) degree from the University of Waterloo, an MBA from XLRI, and a Bachelor of Technology (B.Tech.) in Electrical and Electronics Engineering from NIT Hamirpur. She has also completed a student exchange program at Audencia, where she specialized in Management Consulting and Financial Markets. Snigdha's tech stack includes ML, Data Scientist, SQL, AI, Data Engineering, Python, Hadoop, GCP, Keras, Java, Research Scientist, Spark, Scikit, Big Data, test, Kubernetes, Docker, Tensorflow, and Deep Learning. With her exceptional analytical