Verified recordSoftware Development

Ivan Chandra

Senior Solutions Architect at Tidb, Powered By Pingcap

Based in Jakarta, Indonesia

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Seniority

Staff

Department

Information Technology

Location

Jakarta

Industry

Software Development

Company size

495

Contact information

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Email

1 credit

i•••••••@pingcap.com

Phone

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+62 ••• •••• ••••

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Background

About Ivan Chandra

Summary: Highly skilled and results-driven professional with expertise in cloud computing, data analytics, and machine learning. Possesses a strong technical background and a proven track record of successfully implementing innovative solutions. Demonstrates excellent problem-solving and analytical skills, coupled with a strong ability to communicate complex ideas to both technical and non-technical stakeholders. Committed to continuous learning and staying updated with the latest advancements in the field. Skills: Cloud Computing: Proficient in designing, deploying, and managing cloud infrastructure using AWS platforms. Experienced in utilizing Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) models to architect scalable and reliable cloud solutions. Data Analytics: Skilled in collecting, processing, and analyzing large datasets to derive actionable insights. Proficient in using tools like Python, R, Pandas, SQL, and various BI Tools for data wrangling, exploratory data analysis, statistical modeling, and data visualization. Machine Learning & Deep Learning: Solid understanding of machine learning algorithms, including supervised and unsupervised learning, classification, regression, clustering, and deep learning including neural networks, convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Experienced in building and deploying machine learning and deep learning models using frameworks like TensorFlow, PyTorch, MXNet and Scikit-Learn. Big Data Technologies: Familiar with big data technologies like Apache Hadoop, Spark, and Kafka. Skilled in processing and analyzing large-scale datasets using distributed computing frameworks.

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