Note: The job is a remote job and is open to candidates in USA. Anaplan is seeking a Principal Data Scientist to build and deploy AI capabilities across its enterprise planning platform. The role spans predictive and generative AI, conversational interfaces, and agentic workflows, while providing technical leadership and partnering with Engineering, Product, and Design to bring models into production.
Responsibilities
- Advanced Modeling: Lead the research, design, and implementation of advanced Machine Learning (ML) and Deep Learning (DL) models to solve complex enterprise business problems
- Predictive Analytics: Drive innovation in Timeseries Forecasting, developing robust and scalable models that enhance predictive planning and scenario modeling capabilities
- Generative AI & LLMs: Architect Generative AI solutions, focusing on fine-tuning open-source and proprietary Large Language Models (LLMs) for specialized enterprise data tasks, heavily leveraging Transformer architectures
- Next-Gen Interfaces: Design and integrate Conversational AI interfaces and Agentic AI workflows to create intuitive, autonomous user experiences that can independently execute complex planning workflows
- Collaborate with cross-functional teams (Engineering, Product, and Design) to transition AI models from prototype to robust, scalable production systems
- Technical Leadership: Serve as a subject matter expert, mentoring other data scientists and engineers, and fostering a culture of technical excellence, rigorous testing, and continuous learning
Skills
- 10+ years of hands-on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains
- End-to-end exposure in model lifecycle development, including extensive experience in training and deploying ML models in production environments
- Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns
- Experience in fine-tuning LLMs for domain-specific enterprise applications
- Proficiency in Python and modern software development practices (testing, code review, CI/CD)
- Proven track record of delivering complex technical projects on time with high quality
- Extensive hands-on experience with traditional Machine Learning, Deep Learning techniques, and Timeseries Forecasting algorithms
- Deep technical understanding of Transformer architectures and practical experience fine-tuning LLMs (e.g., LoRA, QLoRA, RLHF)
- Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments
- Experience with agentic frameworks and autonomous agent architectures
- Proficiency in Python and modern software development practices (testing, code review, CI/CD)
- M.S. or Ph.D. in Computer Science, Artificial Intelligence, Statistics, Data Science, or a related quantitative field
- Published research, patents, or significant contributions to open-source projects in the AI/ML community
- 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
- Experience with model observability tools
Benefits
- Hybrid work model for employees who live within commuting distance of one of the offices, with onsite work two days per week.
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