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Gema Parreño leads Data-Driven Apiumhub’s division, facilitating competitiveness in intelligent decision making in the technology industry.
This new business area is accompanied by a renowned Data Science professional, Gema Parreño, who joins the Apiumhub team as Lead Data Scientist.
After consolidating its position as a reference in software architecture, Apiumhub expands its service offering based on data that leads to differentiation and competitive advantage with the help of Gema Parreño, Lead Data Scientist at Apiumhub.
For Apiumhub’s technical team, data-driven projects allow organisations to outsource their analytical needs, as the hierarchy of value creation beyond information is a major challenge for most organisations today. According to data from the European Commission’s 2021 data market study, Spain is among the top five leaders in innovation with a growth rate of 6.5% and 7,133 million in expected revenue by 2025.
Gema Parreño Piqueras is a Spanish data scientist recognised worldwide for having designed Deep Asteroid, a finalist in the NASA International Space Apps Challenge. Gema Parreño rings extensive development experience and contributes to DeepMind’s Pysc2 project, in a discipline called reinforcement learning. Her knowledge and interest in data and artificial intelligence has accompanied her in leading Data and Analytics departments in different companies and entities such as BBVA. The prestigious magazine Business Insider listed her in its list of young leaders of the technological revolution, under 35 years old.
For Gema Parreño, one of the key aspects to solve a data-driven problem is to be clear about the business, product or operational challenge that will constitute the hypothesis to use the data. Therefore, iteration and analysis of the results are fundamental to be able to properly analyse how the different assumptions are made. Data-driven solutions enrich, answer or reinforce business intuitions and business questions.
Recently, Gema Parreño, has started to lead Data-Driven Apiumhub’s area to continue her work focused on Machine Learning First Products. Proof of this is the preparation of use cases that explore the use of Machine Learning applied to the real estate sector and data analysis of the health situation of COVID-19.
Regarding the Machine Learning use case, Gema Parreño predicts the occupancy of a property registered on the AirBnB platform in the city of Barcelona, creating a Machine Learning solution based on the study of the linear dependence and distribution of the data, as well as the possible correlations. Here we would find the logic:
Regarding the data analysis use case, Gema Parreño calculates the progress of herd immunity under the COVID-19 context, investigating the evolution of vaccination over time in each country, analysing which economic factors have influenced the progress of vaccination and identifying logistic growth patterns in order to predict the time to herd immunity. In the following correlation matrix we can see the vaccination characteristics of COVID-19 with data ranging from December 2020 to May 2021 and global economic factors, in order to discover the key economic factors influencing vaccination: