Manager, Data Science (Tech Lead)

As a Data Science Technical Lead Manager (TLM) at Xometry, your primary responsibilities involve leading and managing a team of data scientists, guiding them to achieve high-quality deliverables while providing mentorship. You'll deploy data analysis, visualization, and modeling tools to help strategize cost predictions for our marketplace. Furthermore, you'll design and execute data science projects, collaborating with cross-functional teams to ensure that our data solutions align with Xometry's business objectives.

To qualify for the Data Science Technical Lead Manager role at Xometry, candidates need at least a bachelor's degree, though an advanced degree in fields like applied math or data science is highly preferred. Additionally, you should have over 7 years of experience in data science, including 3 years in a leadership position, strong skills in SQL and Python, proficiency in applied statistics, and experience with pricing algorithms.

The Data Science team at Xometry utilizes a blend of powerful tools and technologies to drive insights. Key among these are Python libraries such as Pandas, numpy, and scikit-learn for data manipulation and analysis. Data visualization is done through tools like Looker, while model development often includes experimentation techniques like A/B testing. Familiarity with databases such as Snowflake and MongoDB is also essential for data extraction.

Collaboration is vital for the Data Science Technical Lead Manager at Xometry, as you will work closely with various cross-functional teams. Your role includes translating complex business needs into actionable data science solutions, ensuring all teams are aligned with Xometry's strategic objectives. This requires effective communication skills to articulate technical information to non-technical stakeholders and foster a spirit of teamwork across departments.

Xometry boasts a vibrant and inclusive work culture, even for remote employees such as the Data Science Technical Lead Manager. We prioritize diversity, equity, and inclusion, creating an environment where every individual feels welcomed, respected, and valued for who they are. You will be part of a collaborative setup that encourages continuous learning and knowledge sharing, allowing you to thrive and innovate in our fast-paced industry.

When discussing your experience in managing data science teams, highlight specific instances where you provided mentorship and direction. Illustrate your leadership style, focusing on how you support team members’ growth while ensuring project goals are met. Use examples that depict your approach to tackling challenges and optimizing team performance.

In response, share the data science methodologies you’ve successfully utilized, such as regression analysis, A/B testing, or machine learning models. Explain why you find them effective, perhaps by citing success stories from previous projects, and relate them back to how they could benefit the team at Xometry.

Discuss your strategy for prioritizing projects by evaluating business impact, urgency, and resources. Share specific frameworks or tools you use for project management and how effective prioritization has led to successful outcomes in your past roles.

Elaborate on your hands-on experience with SQL and Python by describing specific projects where you've used them. Highlight your proficiency in data extraction, manipulation, and analysis, relating back to how this expertise will enhance data solutions at Xometry.

Share concrete examples of how you've encouraged continuous learning in past roles, such as implementing knowledge-sharing sessions, workshops, or mentorship programs. Emphasize the importance of staying updated with industry trends and how you integrate this into your team's growth.

Provide an insightful example of a challenging data science problem you've tackled, detailing the methodologies employed and the results achieved. Focus on how your problem-solving skills could similarly benefit Xometry’s projects.

Discuss your methodical approach to A/B testing, from hypothesis formation to execution and analysis of results. Illustrate how you've used A/B testing to inform critical business decisions in prior roles.

When addressing this question, illustrate your ability to break down complex data insights into digestible narratives. Mention techniques like visualization and storytelling, which you have successfully used to engage non-technical audiences in past experiences.

In answering this question, demonstrate your understanding of Xometry’s business model. Discuss how data science can enhance operational efficiency, inform strategic decision-making, and drive innovation within the marketplace.

Articulate the specific methods you’ve employed for algorithm optimization, including performance evaluation techniques, and adjustments that have led to measurable improvements. Highlight how you would apply these in your role at Xometry.