Data Scientist with NLP and LangGraph

  • Plano, TX
  • Posted 13 hours ago | Updated 13 hours ago

Overview

On Site
Contract - W2
Contract - 1 day((s))

Skills

Python
NLP
TensorFlow
PyTorch
Data Scientist
LangGraph
LSTM
Keras
GPT

Job Details

Job Tittle: Data Scientist with NLP and LangGraph W2 Only!!

Location: Plano, TX (Onsite Position)

Duration: Longterm Contract

Must : F2F Interview

Job Description:
Core Technical Skills

  • Programming Languages: Advanced proficiency in Python (preferred) and/or R; experience with Jupyter notebooks.
  • NLP Libraries & Frameworks: Strong hands-on experience with NLTK, spaCy, Gensim, Hugging Face Transformers, and Scikit-learn.
  • Text Preprocessing: Expertise in processing noisy, unstructured text from various data sources
  • Domain-Specific NLP: Familiarity with entity recognition, intent detection, and text classification
  • Machine Learning: Solid foundation in supervised and unsupervised learning, with applications to telecom problems (e.g., anomaly detection, predictive maintenance, customer segmentation).
  • Deep Learning for NLP: Experience with deep learning frameworks (TensorFlow, PyTorch, Keras) for advanced NLP tasks (LSTM, Transformers, BERT, GPT).
  • Data Handling: Proficient in handling large-scale, high-velocity telecom datasets; experience with distributed data processing (Spark, Hadoop) is a plus.
  • Evaluation: Design and interpret experiments to evaluate NLP models, including error analysis and business impact assessment.
  • Statistical Analysis: Strong understanding of statistics and probability as applied to telecom service quality and customer experience.
  • Azure experience preferred
  • Both positions require hands on experience with Agentic framework
  • Analytical & Problem-Solving Skills
  • Workflow Optimization: Ability to identify bottlenecks in graph-based agent flows and optimize for performance and reliability.
  • Data Handling: Experience with data preprocessing, postprocessing, and evaluation of AI-generated outputs.
  • Evaluation: Design and interpret experiments to evaluate NLP models in a telecom context, including error analysis and business impact assessment.
  • Statistical Analysis: Strong understanding of statistics and probability as applied to telecom service quality and customer experience.
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