Data Scientist • Senior

Who you are

You have a strong background in data science with a focus on machine learning principles — your experience includes developing predictive models that inform business strategies and outcomes. You are proficient in using cloud resources, particularly AWS, to prepare and process data effectively.

Your expertise in programming languages such as Python allows you to write software for data preparation, cleaning, and sampling — you understand the importance of data quality and how it impacts model performance. You are also skilled in querying and extracting data from databases like Snowflake and MongoDB, ensuring that you can access the necessary data for your analyses.

You are familiar with data analysis and visualization tools, including SQL, Jupyter Notebooks, and Looker — these tools help you communicate insights and findings to stakeholders effectively. Your knowledge of probability and statistics enables you to make defensible statistical inferences from data, which is crucial for the role.

You thrive in environments that require continuous learning and iteration — you are comfortable navigating ambiguity and solving complex, uncharted problems. Your collaborative spirit makes you a valuable team member, as you enjoy working with others to achieve common goals.

Desirable

A degree in applied math, computer science, natural sciences, or engineering is preferred — this educational background supports your analytical skills and technical knowledge. Experience with 3D data is a plus, as it aligns with the responsibilities of the cost prediction team.

What you'll do

As a Senior Data Scientist at Xometry, you will be responsible for using data science and machine learning principles to develop effective predictive models — your work will directly impact the company's ability to forecast costs and optimize business outcomes. You will write software to prepare, clean, and sample data, ensuring that the data used in your models is of the highest quality.

You will utilize cloud resources, particularly Amazon Web Services, to prepare and process data efficiently — this will involve setting up data pipelines and leveraging cloud computing capabilities to handle large datasets. Your role will also require you to query and extract data from various databases, including Snowflake and MongoDB, to gather the necessary information for your analyses.

In addition to model development, you will use data analysis and visualization tools such as SQL, Python, Jupyter Notebooks, and Looker to inform business strategy — your insights will help guide decision-making processes across the organization. You will be expected to iterate on solutions rapidly, adapting to new information and challenges as they arise.

You will work closely with cross-functional teams, collaborating with engineers and other data scientists to solve challenging problems — your ability to communicate complex ideas clearly will be essential in this collaborative environment. You will also have opportunities for continuous learning and professional development, as Xometry values growth and innovation.

What we offer

Xometry provides a dynamic work environment where you can make a significant impact on the company's success — you will be part of a team that is dedicated to pushing the boundaries of data science and machine learning. The company encourages a culture of teamwork and continuous improvement, allowing you to grow your skills and advance your career.

You will have access to the latest tools and technologies, enabling you to stay at the forefront of the data science field — this includes opportunities to work with cutting-edge machine learning frameworks and cloud computing resources. Xometry also values diversity and inclusion, ensuring that all team members feel supported and empowered to contribute their unique perspectives.

Overall, this role offers a chance to be part of an innovative company that is shaping the future of manufacturing — your contributions will play a vital role in helping Xometry connect ideas with the resources needed to bring them to life.