Principal AI Data Scientist

Anaplan

Principal Data Scientist optimizing AI solutions across Anaplan's platform and driving innovative decision-making. Collaborating with engineering, product, and design teams focused on scalable AI models.

Posted 6/6/2026full-timeRemote • Pennsylvania • 🇺🇸 United StatesLeadWebsite

ATS Keywords

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Hard Skills

Machine LearningDeep LearningTime Series ForecastingTransformer architecturesprompt engineeringConversational AIautonomous Agentic AIMLOpsLLMOpsPython

Soft Skills

mentoringcollaborationtechnical excellencerigorous testingcontinuous learning

Tools & Technologies

CI/CD pipelines

Industry Keywords

Artificial Intelligencefine-tuning LLMsdomain-specific applicationsscalable deploymentsreliable deploymentsmonitorable deployments

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Lead the research, design, and implementation of advanced Machine Learning, Deep Learning, and Time Series Forecasting models to solve complex enterprise business and planning challenges.
Architect GenAI solutions, focusing on fine-tuning proprietary and open-source Large Language Models (LLMs) via Transformer architectures for specialized enterprise data tasks.
Design and integrate Conversational AI and autonomous Agentic AI workflows to create intuitive experiences that can independently execute complex planning tasks.
Collaborate with Engineering, Product, and Design teams to transition AI models from early prototypes into robust, highly scalable production systems.
Serve as a core subject matter expert, mentoring cross-functional teams and driving a culture of technical excellence, rigorous testing, and continuous learning.

Requirements

What you’ll need

Extensive professional engineering experience across Artificial Intelligence, Machine Learning, or related domains.
Deep technical understanding of Transformer architectures, prompt engineering, and conversational AI patterns, alongside practical experience with autonomous agent frameworks.
Experience fine-tuning LLMs (e.g., LoRA, QLoRA, RLHF) specifically for domain-specific enterprise applications.
Taken responsibility for models from concept to production, utilizing strong MLOps and LLMOps practices to ensure scalable, reliable, and monitorable deployments.
High proficiency in Python and modern software development practices, including rigorous testing, code reviews, and CI/CD pipelines.
Strong hands-on experience in traditional Machine Learning and deep learning techniques, specifically including Time Series Forecasting algorithms.

Benefits

Comp & perks

Our commitment to Diversity, Equity, Inclusion and Belonging (DEIB)
Reasonable accommodation for individuals with disabilities
Opportunities to connect, develop, and succeed