Staff Data Scientist – Decision Intelligence

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    "heading": "Staff Data Scientist – Decision Intelligence",
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    "description_html": "<div class=\"job_description\">\n\t\t\t\t\t<p style=\"line-height:1.38;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">About Xanadu:</span></span></span></span></span></span></p><p style=\"line-height:1.38;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Xanadu&#8217;s mission is to build quantum computers that are useful and available to people everywhere.</span></span></span></span></span></span></p><p style=\"line-height:1.38;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">At Xanadu, we are learners, innovators, researchers, collaborators and problem solvers. We are creating something that has never been built before.&#160; 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&#8217;s most challenging problems and literally change the world. And that is something to be excited about!</span></span></span></span></span></span></p><p style=\"line-height:1.38;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Your role and responsibilities:</span></span></span></span></span></span></p><p style=\"line-height:1.38;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">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&amp;D efforts &#8211; fabrication, device characterization, chip design, system architecture, and software developments &#8211; 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 &#8211; 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:</span></span></span></span></span></span></p><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Own the product vision and roadmap for a cross-domain insights platform spanning research and operations.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Apply AI/ML methods &#8211; including large language models, representation learning, and generative approaches &#8211; to surface patterns, correlations, and anomalies across heterogeneous hardware data.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Design intelligent discovery experiences that go beyond static reporting and traditional BI dashboards &#8211; enabling engineers and decision-makers to interrogate data naturally and uncover non-obvious relationships.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Fuse heterogeneous data sources into unified analytical views.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Define analytical requirements and success metrics that shape how data pipelines are built and how the platform evolves.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Provide technical direction to data engineers and data analysis specialists, ensuring coherent alignment toward the product vision.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Drive adoption by deeply understanding user workflows, iterating on feedback, and shipping incrementally.</span></span></span></span></span></span></li></ul><h2 style=\"line-height:1.38;margin-top:24px;margin-bottom:8px;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Basic qualifications and experience:</span></span></span></span></span></span></h2><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">BSc. in Physics, Mathematics, Computer Science, Data Science, AI, Machine Learning or a related quantitative field.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">7+ years of experience in data science or applied ML, with demonstrated ownership of data-driven products (not just analyses &#8211; you've shipped tools and platforms that people rely on daily).</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Proven ability to unify heterogeneous data sources &#8211; you've built systems that integrate multiple databases, schemas, and data formats into coherent analytical products.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Product mindset &#8211; you think in user problems, adoption loops, and iterative delivery.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Deep comfort with noisy, real-world experimental data &#8211; you understand measurement uncertainty, systematic vs. random variability, and the gap between models and reality.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Strong foundations in statistical modeling and machine learning &#8211; Bayesian inference, hierarchical models, time-series analysis, dimensionality reduction, anomaly detection.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Production-quality Python, SQL, Spark, or other DS stack. Experience building AI-driven analytical tools and integrating ML models into user-facing products.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Excellent communication &#8211; you can present to both PhDs and VPs, translating between technical depth and strategic clarity.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience mentoring or technically leading junior data scientists or analysts.</span></span></span></span></span></span></li></ul><h2 style=\"line-height:1.38;margin-top:24px;margin-bottom:8px;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Preferred qualifications and experience:</span></span></span></span></span></span></h2><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">MSc/PhD in Physics, Applied Mathematics, Computer Science, Data Science, or a related quantitative field.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience in hardware, semiconductor, photonics, electrical engineering, or advanced manufacturing environments.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience with knowledge graphs, semantic data layers, or cross-referencing across complex data ontologies.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience with signal processing, control theory, deep learning, active learning, and optimization.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Exposure to simulation workflows (electromagnetic, circuit-level, or system-level) and their data outputs.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience with cloud infrastructure (AWS preferred) and data pipeline orchestration.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience applying LLMs, retrieval-augmented generation (RAG), or AI agents to data analysis workflows.</span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:11pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Familiarity with quantum computing or photonic integrated circuits.</span></span></span></span></span></span></li></ul><p style=\"line-height:1.656;background-color:#ffffff;margin-bottom:16px;padding:12pt 0pt 0pt 0pt;\"><span style=\"font-size:10.5pt;font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"background-color:#ffffff;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">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.</span></span></span></span></span></span></span></p><p> </p>\n\n<p><span style=\"font-size:12px\"><span style=\"font-family:Arial,Helvetica,sans-serif\">Our values are important. They are fundamental and lay the foundation for culture at Xanadu. Learn more about our values <a href=\"https://www.xanadu.ai/values\">here</a>.</span></span></p>\n\n<p><span style=\"font-size:12px\"><span style=\"font-family:Arial,Helvetica,sans-serif\">We are an equal opportunity employer and encourage candidates of all backgrounds to apply. We are committed to building an inclusive, safe, and equitable culture and fostering an environment where our employees feel included, valued, and heard. We are committed to meeting the needs of all individuals and support a barrier-free workplace. Should you require accommodations at any point during the recruitment process please contact Recruiting at <a href=\"/cdn-cgi/l/email-protection#ff8d9a9c8d8a968b969198d9dcc9cbc4879e919e9b8ad19e96\">recruiting&#64;xanadu.ai</a>. </span></span></p>\n\n<p><span style=\"font-size:12px\"><span style=\"font-family:Arial,Helvetica,sans-serif\">Please be advised that we may use artificial intelligence (AI) tools to assist in the screening and assessment of applicants for this position. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</span></span></p>",
    "description_text": "About Xanadu:\n Xanadu’s mission is to build quantum computers that are useful and available to people everywhere.\n 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!\n Your role and responsibilities:\n 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:\n Own the product vision and roadmap for a cross-domain insights platform spanning research and operations.\n Apply AI/ML methods – including large language models, representation learning, and generative approaches – to surface patterns, correlations, and anomalies across heterogeneous hardware data.\n 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.\n Fuse heterogeneous data sources into unified analytical views.\n Define analytical requirements and success metrics that shape how data pipelines are built and how the platform evolves.\n Provide technical direction to data engineers and data analysis specialists, ensuring coherent alignment toward the product vision.\n Drive adoption by deeply understanding user workflows, iterating on feedback, and shipping incrementally.\n Basic qualifications and experience:\n BSc. in Physics, Mathematics, Computer Science, Data Science, AI, Machine Learning or a related quantitative field.\n 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).\n Proven ability to unify heterogeneous data sources – you've built systems that integrate multiple databases, schemas, and data formats into coherent analytical products.\n Product mindset – you think in user problems, adoption loops, and iterative delivery.\n Deep comfort with noisy, real-world experimental data – you understand measurement uncertainty, systematic vs. random variability, and the gap between models and reality.\n Strong foundations in statistical modeling and machine learning – Bayesian inference, hierarchical models, time-series analysis, dimensionality reduction, anomaly detection.\n Production-quality Python, SQL, Spark, or other DS stack. Experience building AI-driven analytical tools and integrating ML models into user-facing products.\n Excellent communication – you can present to both PhDs and VPs, translating between technical depth and strategic clarity.\n Experience mentoring or technically leading junior data scientists or analysts.\n Preferred qualifications and experience:\n MSc/PhD in Physics, Applied Mathematics, Computer Science, Data Science, or a related quantitative field.\n Experience in hardware, semiconductor, photonics, electrical engineering, or advanced manufacturing environments.\n Experience with knowledge graphs, semantic data layers, or cross-referencing across complex data ontologies.\n Experience with signal processing, control theory, deep learning, active learning, and optimization.\n Exposure to simulation workflows (electromagnetic, circuit-level, or system-level) and their data outputs.\n Experience with cloud infrastructure (AWS preferred) and data pipeline orchestration.\n Experience applying LLMs, retrieval-augmented generation (RAG), or AI agents to data analysis workflows.\n Familiarity with quantum computing or photonic integrated circuits.\n 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.\n Our values are important. They are fundamental and lay the foundation for culture at Xanadu. Learn more about our values here .\n We are an equal opportunity employer and encourage candidates of all backgrounds to apply. We are committed to building an inclusive, safe, and equitable culture and fostering an environment where our employees feel included, valued, and heard. We are committed to meeting the needs of all individuals and support a barrier-free workplace. Should you require accommodations at any point during the recruitment process please contact Recruiting at [email protected] .\n Please be advised that we may use artificial intelligence (AI) tools to assist in the screening and assessment of applicants for this position. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.",
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    "title": "Staff Data Scientist – Decision Intelligence",
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