Description:

Xometry is seeking a Data Scientist II to join their cost prediction team.
The role involves using machine learning tools and techniques to construct, optimize, and evaluate predictive models for various business outcomes.
Responsibilities include developing predictive models using 3D data, preparing and cleaning data, and utilizing cloud resources like Amazon Web Services.
The candidate will query and extract data from databases such as Snowflake and MongoDB.
Data analysis and visualization tools like SQL, Python, Jupyter Notebooks, and Looker will be used to inform business strategy.
The position requires solving challenging problems in a fast-paced environment characterized by ambiguity.
Teamwork and continuous learning are emphasized in the work environment.

Requirements:

A Bachelor’s degree is required, preferably in applied math, computer science, natural sciences, or engineering.
A degree in Mathematics, Statistics, or a related field (M.S. or PhD) is highly desired.
The candidate must have 3+ years of experience with machine learning, statistical modeling, and optimization techniques.
Experience in 3D deep learning, including Mesh, Volumetric, and/or Point Clouds, is a plus.
Proficiency in Python, particularly with libraries such as pandas, numpy, SciPy, and scikit-learn, is required.
A strong understanding of linear algebra and statistics is necessary.
Familiarity with scientific software principles, including versioning systems, reproducibility, and code deployment, is expected.
Experience in the manufacturing industry is desired.
The candidate must be a US Citizen or Green Card holder due to ITAR regulations.

Xometry promotes a diverse, equitable, and inclusive workplace, valuing individuals for their unique contributions.
The company is committed to providing a positive work environment for all employees.
Xometry is an equal opportunity employer, ensuring all applicants are considered without discrimination.
For US-based roles, Xometry participates in E-Verify to confirm work authorization after a job offer is accepted.