Daniel P.
About Daniel P.
Daniel P. is a Data Scientist at TomTom with a background in big data and data science, previously working at Mahou San Miguel and KPMG.
Current Role at TomTom
Daniel P. currently works as a Data Scientist at TomTom, starting his tenure in 2023. He operates in a hybrid setting in Spain. His responsibilities likely include utilizing data science techniques to enhance TomTom's mapping and navigation services. This role allows him to apply his skills in big data workflows and cloud technologies, contributing to the company's innovative solutions.
Previous Experience at Mahou San Miguel
Daniel P. held the position of Data Scientist at Mahou San Miguel from 2021 to 2023. Based in Madrid, Spain, he contributed to the company's data-driven initiatives for two years. During his time at Mahou San Miguel, Daniel likely worked on projects that involved optimizing data processes and applying advanced analytics to support business operations.
Financial Services Consultant at KPMG
In 2021, Daniel P. worked as a Financial Services Consultant at KPMG for nine months in the Community of Madrid, Spain. His role would have involved analyzing financial data, conducting risk assessments, and advising clients on financial strategies. This experience helped him develop a strong analytical foundation and understanding of financial services.
Internship at SANZ Clima
Before his professional career, Daniel P. was an Intern Data Scientist at SANZ Clima from 2020 to 2021. During his one-year internship, he gained hands-on experience in data science projects, contributing to the organization's efforts in climate control and energy efficiency solutions.
Education and Academic Background
Daniel P. holds a Master of Science in Big Data and Data Science from Universidad Autónoma de Madrid, completed between 2021 and 2023. Prior to this, he earned a Degree in Mathematics from Universidad Nacional de Educación a Distancia (UNED), where he studied from 2016 to 2021. His educational background provided a strong foundation in both theoretical and applied aspects of data science and mathematics.
Expertise in Big Data Workflows
Daniel P. has expertise in optimizing big data workflows, particularly using technologies like Apache Spark and Delta Lake. His proficiency in these tools allows him to handle large datasets efficiently, ensuring that data processing and analytics are both scalable and effective. This expertise is critical for his roles in various organizations, where data-driven decision-making is essential.
Proficiency in Cloud Technologies
Daniel P. is skilled in leveraging cloud technologies, including Azure and Databricks. These platforms enable him to deploy, manage, and analyze data in a cloud environment, providing flexible and scalable solutions for data-intensive tasks. His proficiency in these tools supports his work in developing efficient and reliable data science solutions.