The Coolest Data Science and Machine Learning CEOs of 2021

The Coolest Data Science and Machine Learning CEOs

A list of the coolest data science and machine learning CEOs making a difference in a competitive global software market.

Data science is one of the fastest-growing fields in America. Organizations are employing data scientists at a rapid rate to help them analyze increasingly large and complex data volumes. The proliferation of big data and the need to make sense of it all has created a vortex where all of these things exist together. As a result, new techniques, technologies, and theories are continually being developed to run advanced analysis, and they all require development and programming to ensure a path forward.

The chief executive officer (CEO) is the highest-ranked executive in a company. The CEO has many responsibilities, ranging from setting strategy and direction to configuring the company’s culture, values, and behavior. The chief executive is also responsible for building a  leadership team and allocating funds to match the company’s goals and priorities. Some CEOs have even more on their plate, especially those at the head of startups. Oftentimes they are responsible for more than just the traditional duties and can include anything from brewing coffee to marketing their product.

Solutions Review has compiled this list of the coolest data science CEOs based on a number of factors, including the company’s market share, growth trajectory, and the impact each individual has had on its presence in what is becoming one the most competitive global software markets. Some of the coolest data science CEOs have been with their respective companies since day one while others are serial entrepreneurs. One thing that stands out is the diversity of skills that these chief executives bring to the table, each with a unique perspective that allows their company to thrive.

Note: CEOs are listed in alphabetical order.

The Coolest Data Science CEOs

Ali Ghodsi, Databricks

Ali Ghodsi, DatabricksAli is the CEO and co–founder of Databricks, responsible for the growth and international​ ​expansion of the company. He previously served as the VP of Engineering and Product​ ​Management before taking the role of CEO in January 2016. In addition to his work at Databricks, Ali serves as an adjunct professor at UC Berkeley and is on the board at UC Berkeley’s RiseLab. Ali was one of the creators of the popular open-source project Apache Spark as well, Databricks raised $1 billion in pre-IPO funding at a $28 billion-dollar valuation in February.

Dan Wright, DataRobot

Dan Wright, DataRobotDan serves as Chief Executive Officer of DataRobot, the leader in Augmented Intelligence. As CEO, Wright drives the strategic direction of the company to democratize AI, enabling organizations across the globe to solve their most pressing challenges with AI. He has extensive experience driving growth and operational excellence at disruptive technology companies. Prior to joining DataRobot, Wright served as Chief Operating Officer at AppDynamics. During his tenure, he was instrumental in helping AppDynamics increase annual recurring revenue. DataRobot acquired Algorithmia and secured $300 million in Series G funding in July.

Florian Douetteau, Dataiku

Florian Douetteau, DataikuFlorian is the Chief Executive Officer of Dataiku. Florian started working in the startup world at age 20 and hasn’t stopped since. He’s fond of creative writing, playing with real and artificial languages, as well as any board or screen games where he still has a chance to beat his kids. He’s also committed to Paris, a city where he was born, raised, loved, and lives; Florian invests in and helps companies and tech founders as a small contribution to the growing Paris tech ecosystem. Dataiku raised $400 million in Series E funding for enterprise AI in August.

Maor Shlomo, Explorium

Maor Shlomo, ExploriumMaor Shlomo is the co-founder and CEO at Explorium. Explorium offers an automated data science platform that uses AI to automatically connect to data sources and distill the most impactful signals for a predictive question. Users can easily build and deploy models right from the platform, as well as connect to thousands of external data sources so customers can scale use cases. Explorium can be used in a number of different ways. The platform can be deployed as part of your data science pipeline or as a managed service. Explorium followed up its Signal Studio release with $75 million in Series C funding in May.

Timothy King
Follow Tim