Yuval Roditi Dor Email & Phone Number

End-to-end researcher with a delivery-focused, data-driven approach:● Understanding business challenges, acquiring insights into domain-specific data, designing algorithmic solutions, and defining evaluation metrics.● Planned and developed machine learning systems for tabular data with textual fields using a Python framework.● Conducted research on several tasks, including column type annotation (CTA), entity resolution (ER), named entity recognition (NER), and text-to-table conversion.● Utilized classic machine learning techniques, such as regression, boosting, decision trees, dimensionality reduction, and clustering, particularly in situations involving small and imbalanced datasets.● Leveraged natural language processing (NLP) methods, including fine-tuning language models, in-context learning with large language models (LLMs), using embeddings, and resources optimization by combining lightweight model with LLM.

Lead member of the product team responsible for providing comprehensive data science support:● Carried out advanced product analysis using Python, integrating statistical tools and machine learning withenhanced data visualizations using Matplotlib, Seaborn, and Plotly.● Executed a principal persona identification and prioritization study based on system logs, utilizing clusteringmethods and variance partitioning analysis.● Performed use case research by analyzing search chains through the examination of textual patterns andmodeling them as probabilistic graph to understand primary usage patterns.

Leading data integration pipeline projects within a team of data engineers:● Use system logs to identify emerging trends, user behaviors, and market demands that can inform new product features or innovations.● Conducted quantitative analysis on relational databases to map data relationships and integrate multiple sources into a unified schema utilizing SQL and Python across Hadoop, SQL Server, and Oracle platforms.

Intelligence data researcher with a strong analytical approach:● Utilized the unit’s internal querying systems to address various analytical questions using methods such as SNAanalysis, geospatial querying, textual retrieval, graph queries, and web data extraction.● Gained experience with a wide variety of data sources and subdomains.