Xometry is seeking a Senior Data Scientist to join our Data Science team. This person will drive data science initiatives, provide technical guidance when needed, and leverage data to solve complex business challenges. The ideal candidate has a deep understanding of data science methodologies, strong statistical expertise, and proven experience delivering impactful data solutions in a dynamic environment. This is a 1-year contract with the potential for extension.

Responsibilities:

Use data analysis, visualization, and modeling tools (e.g., Looker, Jupyter Notebooks, Python, Pandas) to drive data-driven business strategies, with a focus on cost prediction for a two-sided marketplace. Design and execute data science projects, including hypothesis development, statistical analysis, and experimentation (e.g., A/B testing) to answer key business questions and validate assumptions. Collaborate with cross-functional teams to translate business needs into data science solutions and ensure alignment with Xometry’s objectives. Analyze existing algorithms for accuracy and performance, provide recommendations for optimization, and update production code as necessary. Query and extract data from databases (e.g., Snowflake, MongoDB) to support analysis and model development. Implement robust data science methodologies, emphasizing best practices in code reproducibility, version control, and model deployment. Continuously iterate and improve solutions within a fast-paced, agile environment, addressing challenges with innovative, data-driven approaches. Foster a culture of collaboration, teamwork, and continuous learning, encouraging knowledge sharing and skill development within the team.

Qualifications:

A bachelor’s degree is required; an advanced degree (M.S. or PhD) in applied math, computer science, data science, engineering, or a related field is highly preferred. 5+ years of experience in data science Strong expertise in SQL and Python (numpy, scipy, pandas, and scikit-learn preferred) and experience with API integrations using Python. Proficient in applied statistics, including knowledge of probability distributions, confidence intervals, statistical tests (e.g., t-tests, ANOVA, Chi-Square), and power analysis. Experience with pricing algorithms and technology-driven product development. Knowledge of scientific software principles, including version control, code reproducibility, and deployment practices. Demonstrated ability to work in a fast-paced, ambiguous environment and manage shifting priorities effectively. Must be able to work core hours aligned with US Eastern Time (GMT-5). Strong communication and interpersonal skills to collaborate with global teams and articulate complex technical information to non-technical stakeholders.

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