Data Systems Manager Jobs in Seattle, WA (NOW HIRING)

We are a fusion power company based in Everett, WA, with the mission to build the world's first fusion power plant, enabling a future with unlimited clean electricity. Our vision is a world with clean, reliable, and affordable energy for everyone.

Since Helion's founding in 2013, we have raised $1.5 billion from long-time investors such as Sam Altman, Mithril, and Capricorn Investment Group as well as new investors including Thrive Capital, LightSpeed Venture Capital, SoftBank, and others to propel us forward. Our current prototype, Polaris, has reached record-breaking plasma temperatures of 150 million degrees Celsius (13 keV). Helion is continuing to iterate and on the path to the world's first fusion power plant, Orion.

This is a pivotal time to join Helion. You will tackle real-world challenges with a team that prizes urgency, rigor, ownership, and a commitment to delivering hard truths – values essential to achieving what no one has before. Together, we will change the future of energy, because the world can’t wait.

You will be responsible for developing the data and knowledge foundation that enables engineers to understand, operate, and improve Helion’s fusion systems. In this role, you will partner closely with engineers, scientists, and operators to transform complex experimental and operational data (including machine telemetry, experimental results, and engineering workflows) into structured datasets, knowledge systems, and AI‑enabled tools that support analysis and decision‑making. You will combine data science, knowledge modeling, and applied AI techniques to make fragmented, rapidly evolving information accessible and actionable at scale. This is an onsite role that reports directly to our R&D Manager at our Everett, WA office.

• Analyze experimental and operational data to identify trends, characterize system performance, and generate actionable insights
• Develop data schemas, ontologies, and metadata frameworks to organize and standardize complex technical information
• Design and maintain data pipelines that transform and integrate diverse data sources into analytics‑ready datasets
• Build and evaluate AI‑powered workflows, including retrieval, summarization, and anomaly analysis systems using operational data
• Prototype decision‑support tools for anomaly detection, experiment comparison, and operational reporting
• Define metrics and evaluation frameworks to ensure effectiveness, reliability, and business impact of statistical models and AI solutions

• 7+ years of experience in data science, statistics, machine learning, or a related quantitative field, especially within a hardware, physics, or engineering environment
• Experience working with complex operational, experimental, and time‑series data to generate insights, detect anomalies, and inform engineering decisions
• Proficiency in Python and modern data science tooling, with experience building data pipelines, analytics infrastructure, or production data systems
• Experience developing structured representations of information, including data models, schemas, metadata frameworks, or ontologies
• Familiarity with LLM APIs and applied AI techniques such as RAG, embeddings, semantic search, and AI‑powered workflow automation
• Ability to translate ambiguous problems into practical, scalable solutions and partner effectively with engineers and scientists

• Medical, Dental, and Vision plans for employees and their families
• 31 Days of PTO (21 vacation days and 10 sick days)
• 10 Paid holidays, plus company‑wide winter break
• Up to 5% employer 401(k) match
• Short term disability, long term disability, and life insurance
• Paid parental leave and support (up to 16 weeks)
• Annual wellness stipend

Helion is an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need assistance or an accommodation during the interview process, please let us know.