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# Data Scientist - USA | Remote

- **Company:** TRENT HOEK OUTDOORS LLC
- **Location:** United States (Remote available)
- **Salary:** $140,000
- **Contract:** Permanent contract
- **Skills:** Data Cleansing, Machine Learning, Natural Language Processing, Software Deployment, Feature Engineering, Chatbots, Large Language Models, Multi-Agent Systems, Model Validation, Document Classification
- **Published:** November 5, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pwttniznn5

## About the Role

* Strong expertise in Natural Language Processing (NLP), including text classification and embeddings.
 * Solid understanding of LLM fundamentals and Transformer architecture.
 * Hands-on experience with machine learning modeling, feature engineering, time-series forecasting, data preprocessing, and model evaluation.
 * Experience building and enhancing conversational AI systems, including virtual assistants, intent and entity modeling, and conversation design.
 * Knowledge of multi-agent architectures and agentic AI evaluation methods.
 * Understanding of production deployment and optimization of machine learning and LLM systems, including inference performance, KV caching, latency, and scalability.
 * Ability to attend a face-to-face interview during the selection process.

## Description

3 Dots IT Solutions is seeking a Data Scientist specializing in Conversational AI and Natural Language Processing (NLP) for an investment partner. This is a remote position open to candidates located within the United States. Candidates should be available for a face-to-face interview as part of the selection process., * Build and enhance complex virtual assistants, including conversation design, intent and entity modeling, error analysis, and production improvements.

 * Develop and improve NLP and machine learning solutions, including text classification, embeddings, and models based on Transformer architecture and large language models (LLMs).
 * Perform machine learning tasks such as feature engineering, time-series forecasting, data preprocessing, and model evaluation.
 * Work with agentic AI and multi-agent architectures, including evaluation frameworks, golden datasets, and LLM-as-a-Judge approaches.
 * Support model fine-tuning and continuous improvement of AI systems.
 * Improve the performance of AI models in production through inference optimization, KV caching, latency reduction, scalability, and deployment practices.