Staff Data Scientist – Decision Intelligence

About Xanadu:

Xanadu’s mission is to build quantum computers that are useful and available to people everywhere.

At Xanadu, we are learners, innovators, researchers, collaborators and problem solvers. We are creating something that has never been built before.  What we are doing is extremely hard, the classic moon shot. Few people in their life will be able to be a part of something like this, where if we are successful, the technologies we develop will solve some of the world’s most challenging problems and literally change the world. And that is something to be excited about!

Your role and responsibilities:

As a Staff Data Scientist, you will lead the design and development of a unified decision intelligence product that fuses data from across Xanadu's R&D efforts – fabrication, device characterization, chip design, system architecture, and software developments – into actionable insights for engineers and leadership. You will leverage AI and modern ML techniques as primary tools for pattern discovery, anomaly detection, and insight generation across complex, unstructured, and high-dimensional datasets. This is not a traditional DS role – you will build intelligent, AI-driven analytical experiences that scale with the complexity of our data and accelerate decision-making across the organization. Specifically, you will:

• Own the product vision and roadmap for a cross-domain insights platform spanning research and operations.
• Apply AI/ML methods – including large language models, representation learning, and generative approaches – to surface patterns, correlations, and anomalies across heterogeneous hardware data.
• Design intelligent discovery experiences that go beyond static reporting and traditional BI dashboards – enabling engineers and decision-makers to interrogate data naturally and uncover non-obvious relationships.
• Fuse heterogeneous data sources into unified analytical views.
• Define analytical requirements and success metrics that shape how data pipelines are built and how the platform evolves.
• Provide technical direction to data engineers and data analysis specialists, ensuring coherent alignment toward the product vision.
• Drive adoption by deeply understanding user workflows, iterating on feedback, and shipping incrementally.

• BSc. in Physics, Mathematics, Computer Science, Data Science, AI, Machine Learning or a related quantitative field.
• 7+ years of experience in data science or applied ML, with demonstrated ownership of data-driven products (not just analyses – you've shipped tools and platforms that people rely on daily).
• Proven ability to unify heterogeneous data sources – you've built systems that integrate multiple databases, schemas, and data formats into coherent analytical products.
• Product mindset – you think in user problems, adoption loops, and iterative delivery.
• Deep comfort with noisy, real-world experimental data – you understand measurement uncertainty, systematic vs. random variability, and the gap between models and reality.
• Strong foundations in statistical modeling and machine learning – Bayesian inference, hierarchical models, time-series analysis, dimensionality reduction, anomaly detection.
• Production-quality Python, SQL, Spark, or other DS stack. Experience building AI-driven analytical tools and integrating ML models into user-facing products.
• Excellent communication – you can present to both PhDs and VPs, translating between technical depth and strategic clarity.
• Experience mentoring or technically leading junior data scientists or analysts.

• MSc/PhD in Physics, Applied Mathematics, Computer Science, Data Science, or a related quantitative field.
• Experience in hardware, semiconductor, photonics, electrical engineering, or advanced manufacturing environments.
• Experience with knowledge graphs, semantic data layers, or cross-referencing across complex data ontologies.
• Experience with signal processing, control theory, deep learning, active learning, and optimization.
• Exposure to simulation workflows (electromagnetic, circuit-level, or system-level) and their data outputs.
• Experience with cloud infrastructure (AWS preferred) and data pipeline orchestration.
• Experience applying LLMs, retrieval-augmented generation (RAG), or AI agents to data analysis workflows.
• Familiarity with quantum computing or photonic integrated circuits.

This is for a new position. Your base salary will be determined based on your location, experience, and internal benchmarks. You will also be eligible for equity and benefits.