Remote Data Jobs • LLMs

We are looking for a motivated and detail-oriented NLP Data Scientist with a passion for text mining, machine learning, and natural language processing. This role offers the opportunity to apply advanced NLP techniques to drive innovation and enhance our workforce intelligence capabilities. As part of our team, you’ll collaborate with experienced NLP data scientists and engineers to design, develop, and optimize algorithms and models that power next-generation workforce solutions.

In this role, you’ll drive the development and deployment of AI-powered operational efficiencies and AI-driven product features with a high degree of autonomy. You’ll be responsible for delivering AI agents and prompt engineering that unlocks productivity, enhances decision-making, and elevates the intelligence layer of our proprietary platform. This position blends deep hands-on experience with AI toolchains and a strategic mindset.

Design and build breakthrough approaches and solutions for clients using clinical trial data. As a Senior Data Scientist, you will take ownership for the design, implementation, and support of AI-enabled products for the company’s elluminate software platform. You will need strong analytical and technical skills in classical machine learning (ML), deep learning (DL), and large language models (LLMs). You will work in close collaboration with the company’s business clients and internal stakeholders, including the product and engineering teams. You will also serve as a mentor to other team members as we build AI-enabled products that enhance the experience and efficiency of elluminate users using structured and unstructured clinical trial data.

Join the AI research team at Truveta and contribute to innovative projects in Deep Learning using Structured and Unstructured data that demand cutting edge use of encoding and Transformer based modeling including LLMs. Collaborate with researchers and engineers to design, develop, and refine deep learning models using Structured, Unstructured, and multi-modal data for various applications. Implement, train, and fine-tune deep learning models on large-scale datasets.