Data Science Intern

At ALLEN, we spearhead a technology-driven approach to education, leveraging top-tier tech talent from leading technology firms. Through our strategic collaboration with Bodhi Tree Systems, a prominent venture capital firm known for building & scaling tech-first brands, we are revolutionizing education with a tech-first approach
We address two critical challenges in the current education landscape: the need for more emphasis on holistic learning and adopting a one-size-fits-all approach. We are leveraging AI to develop an innovative ed-tech platform to provide students with a compelling end-to-end learning experience. Our goal is to transform education by providing personalized learning experiences that transcend traditional classrooms by catering to individual learning needs and to drive significant improvements in learning outcomes
Join us in reshaping education for the digital era and unlocking the full potential of every student!
Key Responsibilities
Take part in Design and develop natural language processing systems.
Use effective text representations to transform natural language into useful features.
Develop NLP systems according to requirements.
Train the developed model and run evaluation experiments.
Apply NLP techniques/LLMs to understand grade 12 math, biology, and other subjects.
Tag and generate content like questions, concept cards, video transcripts, etc.
Work closely with NLP Scientists and Software Engineers to deploy NLP models in production.
Remain updated in the rapidly changing field of machine learning.
Qualifications

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Masters degree in computer science, mathematics, computational linguistics or equivalent.
Skills
Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modeling.
Deep understanding of text representation techniques (such as n-grams, bag of words, sentiment analysis etc), statistics and classification algorithms.
Knowledge of Python.
Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).