ME00573-Data Scientist 3

Momentum Engineering, Inc.•Fort Meade, MD

132d•$135,000 - $180,000•Onsite

About The Position

Seeking a Data Scientist to support the development of advanced Natural Language Processing (NLP) solutions focused on the automated processing and analysis of spoken and written language data. This role is responsible for building and improving models that accurately tokenize language data and annotate linguistic features, enabling scalable and high-quality language understanding capabilities. The position involves evaluating model performance against human-generated annotations to continuously enhance accuracy and effectiveness.

Requirements

Must have active Top Secret/SCI clearance with Full Scope Polygraph (MD Customer)
Master’s degree with 6 years of relevant experience, Bachelor’s Degree with 8 years of relevant experience, or Associate's Degree with 10 years of in-depth relevant experience that is clearly related to the position
Experience with Natural Language Processing (NLP) and machine learning techniques
Strong proficiency in Python and relevant NLP/ML libraries (e.g., NLTK, spaCy, Hugging Face, or similar)
Experience developing models for tokenization, text processing, and linguistic annotation
Experience working with speech and/or text data
Understanding of model evaluation techniques, including comparison to ground truth or human-labeled data
Strong analytical and problem-solving skills

Nice To Haves

Experience with part-of-speech tagging and linguistic modeling
Experience working with multilingual or speech-based datasets
Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow)
Experience deploying NLP models in production environments
Knowledge of data pipelines and large-scale data processing

Responsibilities

Develop and implement NLP models to automatically tokenize language data from both spoken and written sources
Design and build automated solutions for annotating language data with parts-of-speech (POS) tagging and linguistic features
Train, test, and validate machine learning models for language processing tasks
Evaluate and improve model performance by benchmarking against human-generated annotations for speech and text data
Process and analyze large volumes of structured and unstructured language data
Develop data pipelines to support ingestion, preprocessing, and transformation of linguistic datasets
Collaborate with cross-functional teams to integrate NLP models into production systems
Perform error analysis and model tuning to improve accuracy and robustness
Document methodologies, model performance, and data processing workflows