Manager-Data Scientist

Posted 21 Days Ago
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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The Company
HQ: New York, NY
30,246 Employees
Year Founded: 1999

What We Do

Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.

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