Data Scientist

Enterprise Holdings•Clayton, MO

1d•Remote

About The Position

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. Success in this position requires strong collaboration with both technical and non-technical teams to ensure the creation, delivery, and adoption of impactful analytical solutions. This position offers the opportunity to work fully remote within the United States (except for Alaska and/or Hawaii). Team members who choose virtual / remote work should have an adequate space to serve as their home office, and must be able to work a schedule within U.S. Central Standard Time core business hours. This position will require employees to come on site to one of our St. Louis campus locations a few times per year for meetings/events or as needed.

Requirements

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 the United States (does not include Alaska or Hawaii).
Must be able to work a schedule within U.S. Central Standard Time core business hours.
Master’s Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics).
Two (2+) years of experience with predictive models, statistical inference and deep learning.
Experience using libraries like tensorflow or pytorch.
Experience preparing and giving presentations to technical and non-technical audiences.
Proficiency in R or Python.
Committed to incorporating security into all decisions and daily job responsibilities.

Nice To Haves

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.).

Responsibilities

Design and deploy advanced deep learning models to forecast demand.
Enable branch-level decision-making to maximize revenue by leveraging historical trends and predictive analytics.
Collaborate with cross-functional teams to develop and implement analytical solutions that drive measurable business impact.
Extract, clean, and manipulate structured and unstructured data from multiple sources.
Perform exploratory data analysis to identify patterns, trends, and insights.
Develop predictive models to support data-driven decision-making.
Design and oversee experiments, ensuring accurate execution and interpretation of results.
Apply causal inference techniques using observational data to uncover relationships.
Prepare and deliver clear documentation of methodologies, findings, and recommendations.
Create and present insightful reports and presentations for technical and non-technical audiences.
Partner with cross-functional teams to implement and operationalize analytical solutions.