Data Scientist

About the role

The Data Scientist is a key driver of innovation, transforming data into actionable insights that improve business processes. In this role, you’ll develop cutting-edge analytical products—creating algorithms for automation, building predictive models, designing experiments, and applying causal inference techniques to observational data. You’ll also harness mathematical optimization to identify the most profitable business strategies.

Responsibilities

• Develop cutting-edge analytical products—creating algorithms for automation, building predictive models, designing experiments, and applying causal inference techniques to observational data.
• Collaborate with cross-functional teams to develop and implement analytical solutions that drive measurable business impact.
• Design and oversee experiments, ensuring accurate execution and interpretation of results.
• Apply causal inference techniques using observational data to uncover relationships.
• Create and present insightful reports and presentations for technical and non-technical audiences.
• Partner with cross-functional teams to implement and operationalize analytical solutions.

Qualifications

• Must be presently authorized to work in the U.S. without a requirement for work authorization sponsorship by our company for this position now or in the future.
• Must reside in St. Louis, Missouri, or immediate surrounding area.
• Must have a Master’s Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics).
• Must have two (2+) years of experience with predictive models, statistical inference and deep learning.
• Must have experience using libraries like tensorflow or pytorch.
• Must have experience preparing and giving presentations to technical and non-technical audiences.
• Must have proficiency in R or Python.
• Must be committed to incorporating security into all decisions and daily job responsibilities.

Preferred

• Doctorate Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics).
• Experience designing experiments.
• Experience exploring and visualizing data.
• Experience using Linux/Unix.
• Experience using SQL.
• Experience working with data (merging, recording, etc.) from a variety of sources/formats.
• Experience working with observational data to attempt causal inference (e.g. matching, weighting, etc.).