dotData is the first and only company focused on delivering end-to-end data science automation for the enterprise. dotData’s fully-automated data science platform speeds time to value by democratizing, operationalizing and accelerating the entire data science process, from raw data ingestion through AI-powered feature engineering to ML models in production.

Industrial

AI/ML

Information Technology

dotData

dotData's headquarters in San Mateo, CA, United States

This department focuses on analyzing and interpreting complex data to drive decision-making and innovation.

Data Science

The Software Engineering Team at dotData is responsible for developing and maintaining the company's end-to-end data science automation platform. This includes collaborating on the design and implementation of software components for data ingestion, AI-powered feature engineering, and machine learning model deployment. The team ensures the platform is scalable, efficient, and user-friendly, while also focusing on quality assurance and continuous integration to deliver high-performance solutions for enterprise data science.

Software Engineering Team

This department focuses on designing, coding, and maintaining software applications to meet organizational needs.

Software Development

The Data Science Team at dotData is responsible for developing and optimizing the company's end-to-end data science automation platform. The team works on automating processes such as raw data ingestion, AI-powered feature engineering, and machine learning model deployment. They aim to democratize and accelerate data science solutions, ensuring that enterprises can rapidly achieve valuable insights from their data.

Data Science Team

This department focuses on leveraging data analytics to enhance customer success and support sales engineering initiatives.

Data and Customer Solutions

The Engineering Team at dotData is responsible for designing and developing the company's fully-automated data science platform. They work on streamlining the entire data science process, from raw data ingestion through AI-powered feature engineering to the deployment of machine learning models in production. Their efforts ensure that the platform is robust, scalable, and user-friendly to help enterprises accelerate their data science initiatives.

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Other teams

Software Engineering Team

Software Development

Data Science Team

Data and Customer Solutions

Engineering Team