Data Scientist

Summary

Enterprise Mobility is a provider of mobility solutions operating brands including Enterprise Rent-A-Car, National Car Rental, and Alamo Rent A Car. The Data Scientist will develop and deploy advanced analytical products, including deep learning and predictive models for revenue management, while extracting and analyzing data, designing experiments, applying causal inference, and partnering with cross-functional teams to operationalize impactful solutions.

Responsibilities

• 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 non-technical audiences
• Partner with cross-functional teams to implement and operationalize analytical solutions

Skills

• 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
• 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
• 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.)

Qualifications

Must Haves

• 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
• 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

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.)

Benefits

• Fully remote work within the United States, except for Alaska and/or Hawaii
• The opportunity to work fully remote within the United States
• Team members who choose virtual / remote work may work from a home office