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Senior Data Scientist, Product Analytics Xometry EMEA & APAC · Lexington, KY
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Xometry EMEA & APAC

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Senior Data Scientist, Product Analytics

🗓️ Posted 2026-09-17 Lexington, KY Hybrid ICT
💰 Salary Not shared 📊 Market NA

About the Company

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. Xometry is looking for a highly analytical and data-driven Senior Data Scientist (Product Analytics) with statistical skills and a passion for data to drive improvements in technology. This role will be pivotal in leveraging data to optimize product performance, drive strategic decisions, and continuously improve our user experience through rigorous testing. You will delve deeply into product data, design and analyze experiments, and provide actionable insights that directly impact our product roadmap. Part of the scope of this role is measuring, experimenting on, and quantifying the impact of one of Xometry's highest-leverage strategic initiatives: the DFM AI + IQE integration with our partner . You will design the metric framework, experimentation strategy, and reporting that tell us whether the embedded experience inside the partner's ecosystem - Designcenter, and Teamcenter - is actually delivering the "science fiction speed" digital thread from ideation to delivery, and how to make it better.

Requirements

  • ● Bachelor's degree in Computer Science, Computer Engineering, Data Analytics, Mathematics, Statistics, Information Systems, Economics, or another quantitative discipline
  • ● 6-8 years of relevant experience
  • ● Strong proficiency in data analysis, statistical modeling, and data visualization
  • ● Proven experience in designing, implementing, and analyzing A/B tests and other experiments
  • ● Solid understanding of statistical significance and hypothesis testing
  • ● SQL is a must. Python is nice to have. Any experience with Looker is also desirable.
  • ● Knowledge of data science concepts and methodologies
  • ● Excellent communication and presentation skills, with the ability to explain complex data insights - including to external partner engineering teams
  • ● Strong analytical and problem-solving skills
  • ● Experience working in a product-driven environment
  • ● Attention to detail and a commitment to data accuracy
  • ● multi-surface / partner-integration analytics: Experience designing experiments and metrics across multi-surface or partner-integrated products (embedded experiences, CAD/PLM integrations, B2B SaaS plug-ins, extension or in-app funnels), including the identity-resolution, attribution, and statistical-power problems that come with low-volume enterprise cohorts.
  • ● CAD/PLM/manufacturing fluency: Familiarity with CAD, PLM, or manufacturing workflows; comfort talking with designers, manufacturing engineers, and partner engineering teams about how they actually use tools day-to-day.
  • ● causal methods at scale: Hands-on experience with quasi-experimental and causal inference methods (difference-in-differences, synthetic control, CUPED, switchback, geo-experiments) for situations where clean A/B isn't feasible - common when the experimental unit is an enterprise account or a designer inside a partner environment.