Witad Awards 2023: Data science professional of the year—María Gómez, RavenPack
Some people run away from or give up on challenges and complex problems. María Gómez is not one of those people—she is persistent and determined, and will not stop until she finds a solution.
Gómez, who has worked at RavenPack for five years and is now its head of data engineering, brings this mentality to her role, where she is involved with a diverse array of projects. These include leveraging big data for the financial industry, and developing a Covid-19 news monitor to help users navigate the amount of information available on the virus during the pandemic.
As someone who is passionate about computer technology, Gómez says at RavenPack she has the chance to work and experiment with some of the most innovative and advanced big data and AI technologies. One example is her work building RavenPack’s research infrastructure that supports data integration from various sources. The research infrastructure is designed to handle large volumes of data and automate complex data processing tasks. It implements tools and processes combining various big data technologies and algorithms to generate data. This allows the data science department to retrieve and analyze data from the data lake and push forward research tasks.
The research infrastructure supported RavenPack in publishing 10 research papers in 2022 on topics such as nowcasting inflation, GDP, workforce intelligence, and ESG controversy. On top of that, the infrastructure implements data pipelines to deliver research output directly to clients.
“What drives me most is the impact our work has—we help organizations to leverage the power of data and make more informed and sustainable decisions,” she says.
RavenPack’s data is used to fuel research in finance, quantitative investment, risk, reputation, and many others. In 2022, research teams published over 300 academic studies using RavenPack datasets.
Gómez is also working on expanding RavenPack’s data cloud computing capabilities by integrating Snowflake into its data science workflows and research data lake. She is developing indicator libraries that work on top of Snowflake to support the reproduction of RavenPack’s latest research insights on the fly.
“This removes technical complexity and facilitates organizations to smoothly incorporate data-driven insights in their daily decision-making,” she says.
Looking ahead, Gómez is motivated to continue learning and improving on her data engineering expertise and also to explore new technologies and approaches to enable RavenPack to assist its clients better and faster.
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