Data Science Experts

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.

A leading AI lab is advancing the frontier of generative AI by training Large Language Models to reason rigorously across quantitative and analytical domains. We're seeking talented Data Scientists with strong analytical and modeling expertise to bring hands-on data science excellence and elevate the quality of our AI training data.

Location Requirements

requiring a commitment of 40 hours per week (during weekdays)

About Cincinnatus LLC

Equal Employment Opportunity

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models. A leading AI lab is advancing the frontier of generative AI by training Large Language Models to reason rigorously across quantitative and analytical domains. We're seeking talented Data Scientists with strong analytical and modeling expertise to bring hands-on data science excellence and elevate the quality of our AI training data. This is a W-2 employment position with Cincinnatus LLC, requiring a commitment of 40 hours per week (during weekdays). This position will be placed at a leading AI Lab as part of their extended workforce. Guide research and engineering teams on data science methodology, statistical inference, and modeling best practices. Design challenging data science tasks and write accurate, well-structured analytical solutions. Evaluate data science tasks and solutions produced by AI systems and other experts; provide clear written technical feedback to improve correctness and rigor. Develop guidelines and evaluation frameworks to assess the quality of statistical reasoning, ML pipeline design, and data analysis approaches. Collaborate with other subject matter experts to ensure consistency and accuracy in training data. 3+ years of professional or research experience in data science, data analysis, statistical modeling, or applied machine learning. Ability to commit to 40 hours per week during weekdays for the duration of the engagement. Prior experience with data annotation, labeling, evaluation, or human feedback collection is a strong plus. Experience with LLMs, AI systems, or agentic workflows; familiarity with agentic frameworks is a plus. Strong written communication skills and the ability to explain analytical decisions and modeling choices clearly. About Cincinnatus LLC: Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. Equal Employment Opportunity: Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

• Guide research and engineering teams on data science methodology, statistical inference, and modeling best practices.
• Design challenging data science tasks and write accurate, well-structured analytical solutions.
• Evaluate data science tasks and solutions produced by AI systems and other experts; provide clear written technical feedback to improve correctness and rigor.
• Develop guidelines and evaluation frameworks to assess the quality of statistical reasoning, ML pipeline design, and data analysis approaches.
• Collaborate with other subject matter experts to ensure consistency and accuracy in training data.
• 3+ years of professional or research experience in data science, data analysis, statistical modeling, or applied machine learning.
• Ability to commit to 40 hours per week during weekdays for the duration of the engagement.
• Prior experience with data annotation, labeling, evaluation, or human feedback collection is a strong plus.
• Experience with LLMs, AI systems, or agentic workflows; familiarity with agentic frameworks is a plus.
• Strong written communication skills and the ability to explain analytical decisions and modeling choices clearly.