Deliverables

📍You will design and implement NLP solutions for processing and analyzing unstructured freeform data, enabling seamless matching to internal structures without the need for formal data scrubbing or normalization processes 📍You’ll work with massive datasets of student behavior data and utilize NLP techniques, such as GPT or similar models, to extract meaningful insights, trends, and patterns from the data 📍Develop efficient data preprocessing pipelines to clean and prepare text data for analysis, including text tokenization, stemming, and handling of noisy or unstructured input 📍Create relevant features and representations from textual data that can be used in trend analysis, classification, and clustering tasks 📍Stay updated with the latest advancements in NLP and machine learning, and incorporate them into the analysis process for improved accuracy and efficiency 📍Implement quality control measures to validate the accuracy and reliability of NLP analysis results, ensuring that actionable insights are derived

About you

📍Proficiency in languages commonly used in NLP and machine learning, such as Python, R, and Java 📍Strong understanding and practical experience with machine learning algorithms, especially those used in NLP 📍Deep learning frameworks like TensorFlow and 📍PyTorch and understanding of neural network architectures used in NLP 📍Experience working with GPT and other transformer models, understanding their architecture and implementation details 📍Familiarity with NLP tasks (such as text classification, named entity recognition, and sentiment analysis) and related tools and libraries (like NLTK, SpaCy)