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Eyal Hashimshoni has extensive work experience in data analysis and research. Eyal is currently working at Windward as a Lead Data Analyst, where they lead research projects and collaborations with Product and R&D teams. In this role, they utilize classical ML models to drive data-driven insights and solutions. Eyal also initiated the Analytics Guild, promoting professional learning and process standardization among analysts company-wide. Eyal is also responsible for addressing analytics needs in the Trading and Shipping vertical.

Prior to Windward, Eyal worked as a Data Analyst at Windward, where they conducted data analysis and research using tools such as Python, SQL, NoSQL, and Spark. Eyal gained diverse experience and insights by working across multiple domains within the company. Eyal also worked closely with the DS team on Machine Learning models pipeline, including data validation and cleaning, pattern and anomalies detection, feature engineering, and model post-processing.

Before joining Windward, Eyal was a Data Science Intern at OKO, where they performed time series analysis and forecasting on satellite-based weather data. Eyal utilized classical and ML prediction models to improve dynamic pricing of crop insurance premiums. Eyal also worked with various python libraries such as Pandas, Statsmodels, Gluonts, Folium, and Keras.

Eyal also has experience as an Air Quality Consultant at Ethos Architecture Planning and Environment, where they led data collection and analysis for transportation, meteorology, and air quality data. Eyal ran air dispersion models and provided actionable recommendations to improve air quality in infrastructure planning projects. Eyal managed research projects, presented findings and recommendations to clients and public organizations, and automized data analysis processes to improve productivity.

Additionally, Eyal worked as a Meteorologist Assistant at the Israel Meteorological Service, where they gained experience in meteorology. Eyal also worked as a Graduate Research Assistant at The Hebrew University of Jerusalem, where they conducted research in the Cloud Physics Laboratory, collecting and analyzing data from satellites, drones, crafts, and surface instruments under the supervision of Prof. Daniel Rosenfeld.

Eyal Hashimshoni has a diverse educational background in atmospheric sciences, meteorology, and data science. Eyal obtained a Bachelor of Science degree with a double major in Earth Sciences (specialized in Atmospheric Sciences) and Biology from The Hebrew University of Jerusalem from 2012 to 2015. Following this, Eyal pursued further specialization by completing a Weather Forecasting Course at the Israel Meteorological Service from 2015 to 2016.

Eyal then returned to The Hebrew University of Jerusalem to pursue a Master of Science degree in Atmospheric Sciences and Meteorology from 2015 to 2017. To enhance their knowledge and skills in data science, Eyal completed the Applied Data Science Specialization from Coursera in March 2020. Prior to that, in November 2019, they also completed the Python 3 Programming Specialization, also from Coursera.

In 2020, Eyal engaged in further education by joining Israel Tech Challenge (ITC), where they focused on the field of data science. However, specific details about the degree or certification obtained during this period are not provided.