Ester G. Jones is a Data Scientist at TyrBit, where she leads the integration of advanced AI models into business intelligence systems. With a strong academic background and a deep focus on natural language processing (NLP) and ethical AI, Ester combines cutting-edge machine learning techniques with a critical understanding of how data can—and should—serve human decision-making. Her work ensures that TyrBit’s data-driven platforms remain both technically sophisticated and socially responsible.
Ester earned her Ph.D. in Machine Learning from Sorbonne University, where her research focused on semi-supervised NLP algorithms applied to multilingual data sources. Her dissertation explored the intersection of machine bias, language representation, and explainability in AI systems—a theme that continues to shape her approach today. During her doctoral years, she collaborated with researchers in computational linguistics, public policy, and AI ethics, contributing to several peer-reviewed publications and presenting at international conferences.
Before joining TyrBit, Ester worked at a data analytics consultancy where she designed and deployed predictive models for global development organizations. She led projects that translated raw data into actionable insight—forecasting resource allocation, monitoring program impact, and improving transparency in reporting systems. In these roles, she became adept at balancing statistical rigor with practical implementation, ensuring that models were not only accurate, but interpretable and fair.
At TyrBit, Ester plays a critical role on the Data Science team, where she architects NLP pipelines that enhance the company’s AI-powered analytics suite. Her projects include sentiment analysis models for customer feedback platforms, automated summarization for enterprise reports, and entity recognition tools that improve data categorization across business domains. She works closely with data engineers and software developers to integrate these tools into scalable, real-time systems that support client decision-making.
Ester is also a vocal advocate for ethical AI practices within the company. She initiated TyrBit’s internal AI accountability framework, helping teams adopt standards around dataset diversity, model transparency, and algorithmic fairness. She conducts regular workshops on responsible model deployment and collaborates with legal and compliance teams to ensure adherence to emerging global AI regulations.
In addition to her technical work, Ester is known for her clarity of communication. She has a talent for translating complex model behavior into insights that non-technical stakeholders can understand and act on. Whether she’s presenting a new classification model to product teams or walking a client through confidence intervals and feature importance, Ester brings both analytical depth and empathy to the table.
Outside of TyrBit, she remains active in the broader AI community. She is a regular reviewer for top-tier conferences and has contributed to open-source NLP libraries. Her recent focus includes exploring large language models and their role in business intelligence, with particular attention to safeguarding privacy and mitigating misinformation risks.
Ester views data as a starting point, not an end. Her goal is not simply to model the world, but to support better decisions in a complex, data-rich environment. Through her work at TyrBit, she continues to push the boundaries of what AI can achieve—responsibly and intelligently.
“Data alone is noise—insight comes from asking the right quesons.”