Data Scientist II, Cost Prediction

Posted 2 Days Ago
Be an Early Applicant
Hiring Remotely in United States
Remote
Mid level
Artificial Intelligence
The Role
The Data Scientist II will develop predictive models using machine learning principles, prepare and clean data, and utilize cloud resources for data processing. Responsibilities include querying databases, applying data analysis, and visualizing results to support business strategies in a collaborative and fast-paced environment.
Summary Generated by Built In

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 adding a Data Scientist II to our cost prediction team. The ideal candidate will have a passion for using machine learning tools and techniques to construct, optimize, and evaluate predictive models that predict the likelihood of different business outcomes. Additionally, this person will use their knowledge of probability and statistics to make defensible statistical inferences from data. 

Responsibilities:

  • Use data science and machine learning principles to develop effective predictive models using 3D data
  • Write software to prepare, clean, and sample data for use in developing predictive models
  • Use cloud resources (e.g., Amazon Web Services) to prepare and process data
  • Query and extract data from databases (Snowflake and MongoDB)
  • Use data analysis and visualization tools (examples include SQL, Python, Jupyter Notebooks, and Looker) to inform the business strategy
  • Relentlessly iterate solutions within a fast-paced environment where ambiguity is the norm
  • Solve challenging, uncharted problems
  • Work in an environment that thrives on teamwork and continuous learning opportunities

Requirements:

  • Bachelor’s degree required; degree in applied math, computer science, natural sciences or engineering preferred
  • Degree in Mathematics, Statistics, or related field (M.S. or PhD highly desired)
  • 3+ years of experience with machine learning, statistical modeling, and optimization techniques
  • Plus if you have experience in 3D deep learning; Mesh, Volumetric, and/or Point Clouds
  • Fluent in Python (pandas, numpy, SciPy, and scikit-learn preferred)
  • Proficient in linear algebra and statistics
  • Familiar with scientific software principals, e.g. versioning systems, reproducibility, code deployment
  • Experience in the manufacturing industry is desired
  • Must be a US Citizen or Green Card holder (ITAR) 

#LI-Remote

Here at Xometry we believe in diversity, equity, inclusion and belonging. We are committed to welcoming, respecting, and valuing people for who they are as individuals, learning from their differences, embracing their uniqueness, and providing a positive workplace for all.

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.

For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Top Skills

Python
The Company
Bethesda, MD
381 Employees
On-site Workplace
Year Founded: 2013

What We Do

Xometry is the leading AI-enabled marketplace for on-demand manufacturing, transforming one of the largest industries in the world. With its proprietary technology, Xometry creates a marketplace that enables designers and engineers to rapidly source high-quality on-demand manufactured parts and assemblies. Xometry's innovative platform also empowers sellers of manufacturing services across the nation to grow their businesses. Xometry’s buyers range from self-funded startups to Fortune 100 companies.

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