The Team

The Data Team at Cometeer exists to help make decisions data-driven. Data is a horizontal team that serves all business units across the company. Cometeer seeks to be data driven at its core and across all business functions. This is a foundational principle that is shared across founders, leadership, and all parts of the organization. The vision is that Cometeer wins in great part due to its ability to leverage data to drive rather than simply measure strategy and execution. The Data Team exists to execute on this vision.

The Role

We are looking for a detail-oriented and analytical deep-thinker to closely partner with non-technical and technical stakeholders. A successful candidate should have a strong quantitative foundation as well as a demonstrated ability to directly own business outcomes end-to-end. You will be one of the first hires on the Data Team, reporting to the Head of Data. 

What you’ll do: 

• Partner with internal teams to leverage data and quantitative methods such as hypothesis testing to enable strategic decision-making and operationalize rapid growth.
• Discover, understand, and integrate disparate data sources from every corner of the business, and structure them into clean data models that fuel self-service analytics for internal teams as well as advanced data science.
• Partner with the engineering team to shape product roadmap, scoping and improving upstream systems and backend data sources.

What we’re looking for:

• You have 5+ years experience in a data science role, using quantitative analysis to solve challenging, real-world problems (background in e-commerce or operations is a plus).
• You have a strong quantitative or technical academic background, such as mathematics, computer science, statistics, economics, finance, or physics. 
• Expert on running SQL in production: you write complex joins and window functions in your sleep; you're experienced in state of the art tools (e.g., GitHub, Fivetran, dbt); and you spearhead best practices (e.g., data unit tests, historization, snapshotting, etc.)
• Experience writing statistical models in Python and/or R (e.g., linear regressions or classifiers).
• Experience modeling data into logical objects and relations, with an eye towards broad accessibility across different skill levels, using modern tools such as Looker or Tableau.
• Track record of building strong relationships with cross-functional partners and executives at multiple levels of technical proficiency.