Principal AI Data Scientist

Principal Data Scientist

We're seeking a versatile Principal Data Scientist who can work across the full stack of Anaplan AI applications, from model integration and prompt engineering to building intuitive user interfaces. In this role, you will have a direct impact on our industry‑leading platform by architecting and deploying cutting‑edge AI solutions that drive intelligent, automated, and forward‑looking decision‑making for our global customers. You will bridge the gap between traditional predictive algorithms and modern generative systems.

• Advanced Modeling & Predictive Analytics:
  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.
• Generative AI Architecture:
  Architect GenAI solutions, focusing on fine‑tuning proprietary and open‑source Large Language Models (LLMs) via Transformer architectures for specialized enterprise data tasks.
• Next‑Gen Interfaces:
  Design and integrate Conversational AI and autonomous Agentic AI workflows to create intuitive experiences that can independently execute complex planning tasks.
• Production & Scale:
  Collaborate with Engineering, Product, and Design teams to transition AI models from early prototypes into robust, highly scalable production systems.
• Technical Leadership:
  Serve as a core subject matter expert, mentoring cross‑functional teams and driving a culture of technical excellence, rigorous testing, and continuous learning.

• 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.
• Background in Computer Science, Artificial Intelligence, Statistics, Data Science, or a related quantitative field.
• Experience working with scalable cloud infrastructure (AWS, GCP, or Azure) and MLOps tools for model training, monitoring, and deployment.
• Background in forecasting, planning, or analytics applications.
• Familiarity with Anaplan or similar enterprise planning platforms.
• Experience with A/B testing and experimentation frameworks for AI features.
• Contributions to open‑source ML projects or research publications.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.