Manager-Data Scientist

JOB DESCRIPTION

Position Overview We are seeking a skilled Data Scientist with a focus on Natural Language Processing (NLP) to join our team. The ideal candidate brings 3+ years of hands-on experience working with text data, building NLP models, and developing production-ready machine learning solutions. This role will focus on analyzing unstructured data, designing and implementing NLP models, and collaborating with engineering teams to deploy scalable solutions.

Please note: United States citizenship is a requirement for this position. This position requires a Public Trust security eligibility determination post-hire.

JOB RESPONSIBILITIES

· Conduct detailed exploratory data analysis (EDA) on structured and unstructured text datasets to derive insights and inform model development.

· Design, build, and evaluate models for a variety of NLP tasks, including:

o Text classification

o Named entity recognition (NER)

o Information extraction from unstructured documents

· Develop and refine regular expressions, traditional NLP pipelines, and transformer-based models to support business use cases.

· Write high-quality, production-grade Python code, following best practices for scalability, testing, and maintainability.

· Apply Generative AI techniques and prompt engineering to enhance automation and downstream applications.

· Collaborate closely with machine learning engineering teams to deploy, monitor, and optimize NLP solutions in production.

· Utilize cloud technologies such as Azure or AWS to build, train, and manage ML workloads.

JOB QUALIFICATIONS

· United States citizenship (required).

· 3+ years of experience in data science, with significant focus on NLP.

· Demonstrated expertise in text-based EDA, NLP model development, and working with unstructured data.

· Strong proficiency in Python and NLP/ML libraries (e.g., spaCy, NLTK, Hugging Face Transformers, scikit-learn).

· Hands-on experience with Generative AI models and prompt engineering.

· Strong understanding of machine learning fundamentals, model evaluation, and experiment design.

· Ability to translate business needs into technical solutions and communicate complex concepts effectively.

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Preferred Qualifications

· Experience deploying NLP solutions in production environments in partnership with ML engineering teams.

· Hands-on experience with cloud platforms, including Microsoft Azure or Amazon Web Services (AWS).

· Familiarity with CI/CD workflows, containerization (e.g., Docker), or distributed computing frameworks.

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