Xometry is seeking to leverage advanced statistical modeling and machine learning to understand short-term and longer-term pricing and sourcing dynamics at play in their custom manufacturing marketplace
Requirements
- 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)
- 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
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
- 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
- Assess competitive pricing trends, market dynamics, and customer behavior to generate strategic insights and drive business growth
- Collaborate across teams and clearly communicate insights to both technical and non-technical stakeholders, shaping strategy at the leadership level
Other
- Ability to translate data insights into business recommendations
- Strong communication skills, comfortable presenting technical findings to executive stakeholders
- Bachelor's degree in Applied Math, Computer Science, Statistics, Engineering, or a related field (Master's or Ph.D. strongly preferred)
- 5+ years of experience in Data Science, Machine Learning, or Applied Econometrics
- Ability to work in a hybrid environment
