At some point in our careers, we are asked to “stretch” beyond our core strengths—and then quickly scour all available resources to get up to speed.

With more organizations leveraging AI for better, data-driven decision-making, these “stretch” opportunities are a daily reality for many. A study published by Element AI in 2018 estimated that only 22,000 researchers in the world are able to pursue serious machine learning research.[1] As talent gaps compete with rising demands, we’ve seen the emergence of the “citizen data scientist.” A citizen data scientist is usually someone with a strong technical acumen who, while not a data scientist by training, relies more and more on self-service analytics and AI tools—the superpowers we need to thrive today.

Empowering Citizen Data Scientists

The role of the citizen data scientist has become more prominent over the last few years.[2] Many started out as domain experts and supplemented their skillsets by learning new business intelligence and analytics capabilities. Examples include business intelligence analysts who write macros to gain insights from data hidden in their spreadsheets, intelligence analysts who cobble together open-source projects to ArcGIS to ensure they found all the objects in a satellite image, or the researcher who uses a scanner and OCR algorithm to digitize old records instead of retyping them. While they might not be data scientists by trade, their domain expertise affords them the ability to identify use cases that could benefit from AI.

Since advanced data scientists are hard to hire and retain, organizations must do more to help citizen data scientists be successful.

Modzy was built to empower data science teams with varying levels of technical expertise. Citizen data scientists gain access to push-button implementation of sophisticated AI capabilities, and an easy way to manage the most challenging and tedious parts of the deployment process—which frees advanced data scientists and development teams to focus on what they do best.

Two main ways Modzy helps citizen data scientists

For starters, pre-trained models can help reduce the resources it takes to train new models from scratch, such as training data and computational power. The Modzy model marketplace contains 100+ pre-trained models developed by leading machine learning companies. Models span a wide range of use cases—including text or language-based analysis, object detection or classification, audio and video transcription, and much more.

All models undergo a rigorous review process, so they’re vetted to meet Modzy’s high standards of trustworthiness. And all models are available via the user-friendly Modzy API which requires a minimal amount of code for citizen data scientists to incorporate AI into their workflows. They don’t need to be experts in deep neural networks and other AI-enabling techniques.

Next, ModelOps tools provide the foundation for long-term AI management. Organizations can leverage their own private instance of the Modzy platform as the centralized governance and management solution for all AI models deployed into production. Modzy’s automated approach enable data science teams to build and train powerful models and to see models, workflows, and other projects, so they won’t duplicate resources.

With an assortment of ready-to-use models, as well as a secure, streamlined path for model deployment, data science teams of all dimensions find common ground. Organizations can ensure their AI models are consistently available for widespread adoption, conserving resources while preserving knowledge. Incorporating Modzy into your enterprise applications is a sure-fire way to increase AI ROI and be the hero your organization needs now.

[1] The Global AI talent pool going into 2018, Element AI.

[2] Citizen Data Science Augments Data Discovery and Simplifies Data Science, Gartner Research.