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Elizabeth Keleshian

Ready for new ML opportunity

Elizabeth Keleshian is an ML engineer with a specialization in Natural Language Processing (NLP) and a keen interest in developing solutions on a large scale.

With over two years of experience in ML for NLP within the bustling Bay Area startup ecosystem, Elizabeth's expertise spans text classification, entity recognition, and recommendation engines.

She actively contributes to open-source projects like Mozilla's Common Voice initiative, showcasing her commitment to community-driven development.

Proficient in Python and Javascript, Elizabeth's technical toolkit includes a range of data science and machine learning libraries such as scikit-learn, fasttext, keras, and huggingface.

Moreover, she is well-versed in data manipulation using libraries like sqlite, postgresql, numpy, pandas, spacy, and nltk, enabling her to extract valuable insights from complex datasets.

Elizabeth's educational background is diverse, having pursued a Bachelor's degree in Math/Econ and Philosophy at the University of California, Los Angeles, followed by a Master's degree in Urban Education and Leadership from the University of Pennsylvania.

Her professional journey includes roles at prominent organizations like Way2B1 and Data Science Retreat as a Data Scientist, along with a significant contribution as a Corps Member at Teach For America.

Elizabeth Keleshian
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Location

United States