.Founded in 2016 by a small team, Quantexa was built with a vision of enabling better decision making through better data-driven intelligence. Seven years, twelve locations and 700+ employees later we recently gained "Unicorn" status with our Series E funding round. We've just completed our first acquisition, combining Aylien's advanced AI and Natural Language Processing (NLP) into our Decision Intelligence Platform.Our new NLP Centre of Excellence addresses one of the most challenging problems in Artificial Intelligence: teaching machines to understand natural language. We build products to help people extract meaning and insight from text, while also conducting exploratory research that we believe will drive improvements in our products and advance the state-of-the-art. Some examples of NLP areas that are relevant to our products are entity extraction and resolution, semantic embeddings, classification, information extraction, and clustering. The NLP team also leverages recent advances in Generative AI and Large-Language Models (LLMs) in a variety of ways.As an NLP data scientist, you will be responsible for developing models and prototypes for new and expanded NLP-based product features.You will guide data-driven projects through the entire prototyping phase, from conceptualization and design, until they are ready to be productionized. You will also be responsible for improving models and tracking evaluation metrics for our existing ML products. Where possible you will connect Quantexa's work to relevant threads in NLP and ML research.ResponsibilitiesParticipate in research projects to advance the state-of-the-art in natural language understanding.Design, implement and evaluate machine learning models.Conduct research to improve our NLP products and collaborate with Product and Engineering teams to take ideas from design through to production.Report and present research findings and developments clearly and efficiently both internally and externally, verbally and in writing.Suggest and engage in team collaborations to meet research goals.Minimum qualificationsBachelors or Masters degree in Computer Science or a related technical field, or equivalent practical experience, PhDs also welcome!Relevant experience in Natural Language Understanding, Machine Learning, Data Mining or Artificial Intelligence.Strong knowledge of the Python data-science ecosystem, and general software engineering skills (experience with version control systems, debugging, testing, etc.).Preferred additional qualificationsFirst-author publications at peer-reviewed AI conferences (e.G. NeurIPS, ICML, ICLR, EMNLP and ACL).Strong knowledge of the relevant scientific Python stack: NumPy, SciPy, scikit-learn, TensorFlow, PyTorch, PySpark, etc.Experience with Deep Learning.Experience integrating the results of research into user-facing products
