Manager-Data Scientist

Posted Yesterday
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Hiring Remotely in United States
Remote
Mid level
Information Technology • Database • Consulting
The Role
Build and deploy NLP solutions: perform EDA on text, design and evaluate models (classification, NER, information extraction), develop pipelines from regex to transformers, apply generative AI and prompt engineering, write production-grade Python, and collaborate with ML engineering to deploy and monitor scalable cloud-based solutions.
Summary Generated by Built In

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.

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.

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.


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.

Skills Required

  • United States citizenship
  • Public Trust security eligibility determination (post-hire)
  • 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
  • Experience with NLP/ML libraries (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 write production-grade, testable, maintainable Python code for scalable systems
  • Utilize cloud technologies to build, train, and manage ML workloads (Azure or AWS)
  • Experience deploying NLP solutions in production with ML engineering teams
  • Familiarity with CI/CD workflows, containerization (e.g., Docker), or distributed computing frameworks
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