Scismic

Senior Data Scientist, NLP/LLM Specialist

Scismic

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $155,000 - $240,000 per year

Job Level

Senior

Tech Stack

AirflowApacheAWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchSparkSQLTensorflow

About the role

  • Lead client workshops and discovery sessions to identify NLP opportunities
  • Develop and present technical proposals to C-level executives
  • Manage multiple client projects simultaneously while maintaining quality and timelines
  • Design and implement novel NLP solutions for complex business problems
  • Architect scalable solutions for processing and analyzing large text corpora
  • Build custom language models tailored to each client's unique industry challenges
  • Automate repetitive analytical tasks and develop reusable algorithmic frameworks
  • Mentor junior data scientists and provide technical guidance on NLP projects
  • Develop automated content analysis, document processing, and customer insight systems
  • Create scalable text analytics platforms that drive measurable business outcomes
  • Work across retail, finance, healthcare, and media sectors
  • Translate complex AI capabilities into clear business value propositions

Requirements

  • PhD in Computer Science, Computational Linguistics, Statistics, Mathematics, Economics, Econometrics, or related quantitative field
  • Minimum 5 years of professional experience in data science, machine learning, or related roles
  • Advanced NLP expertise: Deep understanding of transformer architectures, attention mechanisms, and modern NLP techniques
  • Large Language Model proficiency: Hands-on experience with LLM fine-tuning, prompt engineering, RLHF, and deployment at scale
  • Programming mastery: Expert-level Python, with strong knowledge of PyTorch/TensorFlow, Hugging Face ecosystem
  • MLOps & Infrastructure: Experience with model deployment, monitoring, and scaling in production environments
  • Experience writing production code and ensuring well-managed software delivery
  • Experience with foundation models (GPT, BERT, T5, LLaMA, etc.)
  • Knowledge of retrieval-augmented generation (RAG) systems
  • Understanding of model compression techniques (quantization, distillation, pruning)
  • Experience with evaluation metrics and benchmarking for language models