W2 Role - No c2c

Local to MO only

Job Description:

As a Data Scientist focused on revenue management, candidates will design and deploy advanced deep learning models to forecast demand.

These models will enable branch level decision-making, helping maximize revenue by leveraging historical trends and predictive analytics.
In this role, candidates will collaborate closely with cross functional teams to develop and implement analytical solutions that drive measurable business impact.
Collaborate with the team to design and deliver analytical solutions that drive 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 nontechnical audiences.
Partner with cross functional teams to implement and operationalize analytical solutions

Required:

Must be presently authorized to work in the U.S. without a requirement for work authorization sponsorship by client’s 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 nontechnical 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.)

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