Data Scientist; NLP​/Topic Modeling

Overview

Our client is one of the nation’s largest telecommunications and media providers, delivering cutting-edge broadband, entertainment, and technology. With a focus on innovation, scale, and customer experience, the company continues to lead in connectivity, digital transformation, and next-generation AI adoption.

The Data Science team plays a critical role in driving this innovation—leveraging advanced Natural Language Processing (NLP) and Machine Learning to build intelligent systems that optimize operations, enhance customer engagement, and elevate overall service quality.

You’ll join a forward-thinking AI & NLP team responsible for developing an internal generative AI platform designed to streamline how customer interactions and escalation tickets are analyzed and resolved.

The newest initiative focuses on automating customer escalation management
, aggregating tickets from multiple channels (call centers, NPS feedback, support systems), and using ML models to intelligently classify, prioritize, and delegate issues for faster resolution.

As a Data Scientist specializing in NLP and Topic Modeling
, you’ll lead the design, development, and deployment of classification models that transform unstructured customer data into actionable insights. You’ll work closely with ML Engineers, business partners, and data stakeholders to ensure scalable, production-ready solutions that directly improve customer satisfaction and operational efficiency.

• 1. Topic Modeling & Taxonomy Development
  • Lead exploratory data analysis, text clustering, and taxonomy creation to define resolution categories.
  • Develop and validate topic models (e.g., LDA, clustering) to uncover emerging customer issues and trends.
  • Collaborate with business and technical teams to refine taxonomies and ensure alignment with real-world operations.
  • Design and implement NLP-based classification models (traditional or GenAI) to map textual inputs to resolution categories.
  • Build models that handle both voice-to-text transcriptions and technician-generated tickets
    .
  • Optimize accuracy, scalability, and performance across large, diverse datasets.
  • Partner with ML Engineers to product ionize models within existing CI/CD pipelines.
  • Create and maintain performance dashboards, monitoring key accuracy and drift metrics.
  • Continuously refine models based on feedback, error analysis, and live performance data.
• 4. Cross-Functional Collaboration
  • Work closely with data engineering teams on ingestion, transformation, and data readiness.
  • Present model insights, explainability reports, and performance findings to non-technical stakeholders.

• NLP / LLM Expertise: Strong background in topic modeling, text classification, clustering, and generative AI concepts.
• Programming: Proficiency in Python
  , Py Spark , and common ML frameworks (scikit-learn, pandas).
  Scala/Spark exposure a plus.
• Cloud: Familiarity with AWS (S3, EC2, EMR); experience with Azure LLM hosting is a plus.
• MLOps:
  
  Experience with
  CI/CD for ML pipelines
  , model monitoring, and data version control.
• Data Visualization: Skilled at creating visual narratives and analytical dashboards for complex datasets.

• Expertise in SQL & Python – strong experience in both
• 5+ years of hands-on experience in Data Science, NLP, or Machine Learning
  .
• Proven expertise in topic modeling, clustering, and large-scale data processing.
• Strong mathematical and statistical foundation.
• Demonstrable Git Hub portfolio or equivalent showing NLP or AI project work.
• Excellent communication skills with the ability to translate technical insights into actionable business strategies.

“Skills, experience, and other compensable factors will be taken into account when determining pay rate. The pay range provided in this posting is a reflection of a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range.”

“W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick me if required by law in the worked-in state/locality.”

Note:

This job description includes benefits and employment details.