Principal Data Scientist: GenAI, Time Series & Enterprise AI

AI Chopping Block, Inc.; New York (NY); Hybrid; USD 257,000 - 348,000; Full time

Job summary

Anaplan seeks a Principal Data Scientist to work across AI applications, from model integration to user interfaces. You will deploy cutting-edge AI solutions that enable intelligent, forward-looking decision-making for global customers, bridging traditional models and generative systems.

The role emphasizes technical leadership, cross-functional collaboration, and scaling AI into production with rigorous testing and observability. Hybrid work with onsite two days weekly is expected.

Qualifications

• 10+ years of hands-on AI/ML experience.
• Experience with end-to-end model lifecycle in production.
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
• Experience fine-tuning LLMs for domain-specific applications.
• Proficiency in Python and software development practices (CI/CD).
• Track record delivering complex technical projects on time.

Responsibilities

• Lead research, design, and implementation of advanced ML/DL models.
• Drive timeseries forecasting and predictive analytics for enterprise planning.
• Architect Generative AI solutions using open-source and proprietary LLMs.
• Design Conversational AI interfaces and autonomous agent workflows.
• Collaborate with cross-functional teams to productionize AI models.
• Mentor data scientists and engineers, promoting technical excellence.

Skills

AI/ML expertise

LLMs & Prompting

Python proficiency

MLOps & LLMOps

Transformer architectures

Production deployment

Leadership

CI/CD

Education

MS/PhD in CS/AI/DS

Tools

LLM APIs

MLOps tools

Cloud infrastructure

Job description

Anaplan seeks a Principal Data Scientist to work across AI applications, from model integration to user interfaces. You will deploy cutting-edge AI solutions that enable intelligent, forward-looking decision-making for global customers, bridging traditional models and generative systems.

The role emphasizes technical leadership, cross-functional collaboration, and scaling AI into production with rigorous testing and observability. Hybrid work with onsite two days weekly is expected.