Overview
Data Scientist Jobs in United States at Jobright.ai
Title: Data Scientist
Company: Jobright.ai
Location: United States
Jobright is your personal AI job search agent that transforms the job search process into a fast, expert-guided journey. They are seeking a Data Scientist to build and scale business-facing AI agents, managing the entire lifecycle from prototype to production.
Why Join Us
- Your models will power AI agents used by real people navigating real career decisions
- High degree of ownership over both research direction and production outcomes
- Sit at the crossroads of applied ML, generative AI, and consumer product
- Shape the data-driven intelligence behind a new kind of job search experience
Responsibilities
- Build and deploy predictive models and machine learning algorithms that form the analytical backbone of our production AI agents
- Run structured experiments on LLM prompting strategies, fine-tuning approaches, and RAG pipeline configurations to drive measurable improvements in agent quality
- Conduct in-depth statistical analysis of user interaction data to surface behavioral patterns that inform feature development and product strategy
- Track model health in production and provide hands-on technical support through key iteration and release cycles
Qualifications
Required
- Recent grad or early-career professional (0–2 years) with a degree in Data Science, Computer Science, Statistics, or another quantitative discipline
- Strong Python fundamentals and working proficiency with ML libraries such as PyTorch, TensorFlow, or Scikit-learn
- Solid understanding of LLM architectures, prompt engineering principles, and generative AI evaluation techniques
- Clear, confident communicator – able to walk both technical and non-technical collaborators through complex modeling decisions and findings
- Must be based in and authorized to work in the United States
Preferred
- Prior internship or research experience in NLP, autonomous agent development, or recommendation systems
- Hands-on experience building data pipelines and working within cloud environments such as AWS, GCP, or Azure
- Proficiency in SQL and database querying for efficient data extraction and feature engineering workflows
