Xometry
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.
Senior Data Scientist – Pricing and Sourcing Science
is sought to leverage advanced statistical modeling and machine learning to understand short-term and longer-term pricing and sourcing dynamics in our marketplace. Coupled with rigorous experimentation, you will build scalable and adaptive decision-making systems that power core features of our custom manufacturing marketplace. Responsibilities: Develop and implement statistical and machine learning models to optimize pricing, lead times, and sourcing strategies. Design and evaluate experiments (A/B tests, multi-armed bandits, contextual bandits) to enable data-driven decision-making. Assess competitive pricing trends, market dynamics, and customer behavior to generate strategic insights and drive business growth. Build and maintain scalable data pipelines with a focus on code quality, reproducibility, and best practices for deployment. Utilize cloud platforms (AWS, GCP, or Azure) to efficiently process and model large-scale datasets. Collaborate across teams and clearly communicate insights to both technical and non-technical stakeholders, shaping strategy at the leadership level. Qualifications: Education: Bachelor’s degree in Applied Math, Computer Science, Statistics, Engineering, or a related field (Master’s or Ph.D. strongly preferred). Experience: 5+ years of experience in Data Science, Machine Learning, or Applied Econometrics. Proven track record developing predictive and causal inference models, preferably in pricing, marketplace, or supply chain contexts. Experience with experimental design and statistical inference in real-world business settings. Technical Skills: Proficiency in Python (pandas, NumPy, SciPy, scikit-learn, TensorFlow/PyTorch preferred). Strong SQL skills and experience querying large-scale data platforms (e.g., Snowflake, Redshift). Familiarity with scientific software principles (version control, reproducibility, testing). Experience with cloud computing (AWS preferred). Business & Communication: Ability to translate data insights into business recommendations. Strong communication skills, comfortable presenting technical findings to executive stakeholders. Preferred Qualifications: Experience in the Manufacturing or Logistics Industry: Familiarity with the unique challenges and opportunities within these industries. LI-Hybrid Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.
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is sought to leverage advanced statistical modeling and machine learning to understand short-term and longer-term pricing and sourcing dynamics in our marketplace. Coupled with rigorous experimentation, you will build scalable and adaptive decision-making systems that power core features of our custom manufacturing marketplace. Responsibilities: Develop and implement statistical and machine learning models to optimize pricing, lead times, and sourcing strategies. Design and evaluate experiments (A/B tests, multi-armed bandits, contextual bandits) to enable data-driven decision-making. Assess competitive pricing trends, market dynamics, and customer behavior to generate strategic insights and drive business growth. Build and maintain scalable data pipelines with a focus on code quality, reproducibility, and best practices for deployment. Utilize cloud platforms (AWS, GCP, or Azure) to efficiently process and model large-scale datasets. Collaborate across teams and clearly communicate insights to both technical and non-technical stakeholders, shaping strategy at the leadership level. Qualifications: Education: Bachelor’s degree in Applied Math, Computer Science, Statistics, Engineering, or a related field (Master’s or Ph.D. strongly preferred). Experience: 5+ years of experience in Data Science, Machine Learning, or Applied Econometrics. Proven track record developing predictive and causal inference models, preferably in pricing, marketplace, or supply chain contexts. Experience with experimental design and statistical inference in real-world business settings. Technical Skills: Proficiency in Python (pandas, NumPy, SciPy, scikit-learn, TensorFlow/PyTorch preferred). Strong SQL skills and experience querying large-scale data platforms (e.g., Snowflake, Redshift). Familiarity with scientific software principles (version control, reproducibility, testing). Experience with cloud computing (AWS preferred). Business & Communication: Ability to translate data insights into business recommendations. Strong communication skills, comfortable presenting technical findings to executive stakeholders. Preferred Qualifications: Experience in the Manufacturing or Logistics Industry: Familiarity with the unique challenges and opportunities within these industries. LI-Hybrid Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.
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