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Liquidnet Makes Strategic Additions to its Data Science Team

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Company appoints Head of NLP and Unstructured Data and hires three new data scientists, signaling further investment in developing AI-centric tools designed to alert users to key factors influencing their investments.

Liquidnet, the global institutional investment network, today announced the appointment of Steven Nichols as Head of NLP (National Language Processing) and Unstructured Data. Additionally, the company has added three new data scientists – Dr. Nicholas Burtch, Dr. Anthony Schramm and Yusong Liu – to its fast-growing team.

Nichols joined Liquidnet through Liquidnet’s 2019 acquisition of the NLP technology company Prattle, where he was a Director of Data Science. He has been instrumental in the development of Liquidnet’s NLP capabilities and their integration into the Liquidnet Investment Analytics product suite, combining AI tools like machine learning and NLP with traditional and alternative data to help uncover the actionable insights hidden within data and content. In his new role, he will guide the strategic direction of the NLP team while serving as one of the leaders on the Liquidnet data science team. Nichols will report to Liquidnet’s Chief Data Scientist, Tom Doris.

Over the last two years, Liquidnet has made extensive investments in its data science capabilities, with the aim of democratizing access to AI tools which empower individuals in investment and execution decision making. These investments continue to underpin the Liquidnet Investment Analytics product suite.

“We’re committed to building out the deepest data science capabilities possible to help asset managers navigate a complex trading and investment environment. With these new additions and with Steven at the helm, our NLP expertise will grow even stronger,” says Doris.

“NLP is increasingly becoming one of the industry’s favorite AI tools, especially as more managers seek to parse rapidly-growing volumes of unstructured data in an efficient manner. We’re seeing increasing demand for NLP based AI tools like our central bank and equity sentiment scoring products that quantify language patterns, providing previously unavailable quantitative signals. Our goal is not just to make NLP more powerful, but to make it more widely available to firms across various sizes and strategies,” adds Nichols.

Dr. Burtch is a former recipient of the prestigious Harry S. Truman Fellowship and NSF Graduate Fellowship; his research has been published in multiple journals. Dr. Schramm was most recently a Graduate Research Fellow at Yale University and a Fellow at The Data Incubator in New York City. Liu joins Liquidnet from the University of Washington (Seattle), where he earned his master’s degree and oversaw projects on sentiment analysis using neural methods. All three join Liquidnet with deep experience in natural language processing, quantitative analysis, machine learning, data visualization and algorithm development.

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