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Hertz

Car rental services and fleet management

Senior Data Scientist - Fleet Planning

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeEstero, FL, USA$100k - $125kIn-person

About the Job

Requirements

  • A bachelor's degree or higher in Computer Science or another quantitative field such as Statistics, Mathematics, Physics, or Engineering.
  • At least 5 years of hands-on experience in a data science or data analytics role.
  • At least 2 years of intensive experience with cloud-based Big Data, machine learning, and analytics technologies; Databricks experience is preferred.
  • A demonstrated record of delivering data science or machine learning solutions across multiple lifecycle stages, including problem definition, data preparation, modeling, evaluation, implementation, and post-deployment performance assessment.
  • Strong understanding of supervised and unsupervised learning, feature engineering, model selection, statistical evaluation, and diagnosing training, inference, and data-quality issues.
  • Strong Python skills and practical experience with common data science and machine learning libraries such as pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow.
  • Practical experience using AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot, or Databricks Genie to accelerate coding, analysis, and documentation, with the judgment to review, test, and harden AI-generated outputs.
  • Experience with scalable data pipelines, cloud data platforms, and production or near-production analytical workflows.
  • Strong SQL skills with structured and semi-structured data, and experience with data visualization tools such as Tableau.
  • A demonstrated interest in learning, testing, and responsibly applying emerging AI and data science capabilities.
  • A proven record of identifying and diagnosing problems and solving complex ones with simple, logical solutions.
  • Verbal, written, presentation, and facilitation skills to explain technical and non-technical concepts across organizational levels.
  • Interpersonal skills and a track record of building relationships across teams.
  • Ability to operate in a fast-paced environment, manage ambiguity, and adjust to changing priorities and technologies.

Responsibilities

  • Use analytical and machine learning methods to dissect complex business problems and build descriptive, predictive, and prescriptive models that turn data into actionable insight and drive measurable impact for new products and services.
  • Own the end-to-end data science and machine learning lifecycle, from problem framing and feature engineering through experimentation, offline evaluation, production deployment, monitoring, and iteration based on real-world performance.
  • Build simulation environments used to train and evaluate sequential decision-making methods, including reinforcement learning where appropriate, with attention to simulator fidelity, reward design, and offline and online evaluation.
  • Use approved AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot, and Databricks Genie to accelerate analysis, coding, testing, and documentation; critically review, test, and harden AI-generated code and outputs for accuracy, security, reproducibility, and compliance with organizational standards.
  • Explore and prototype generative AI and agentic AI solutions where they fit the business problem, including retrieval-augmented generation, structured data interaction, tool-using agents, workflow automation, decision support, and natural-language interfaces; put evaluation, guardrails, security controls, and human oversight in place before production use.
  • Define success and performance metrics for current and new business initiatives, with particular focus on A/B tests.
  • Design and maintain robust ETL processes that keep data accurate and accessible, and oversee the upkeep and optimization of existing pipelines and dashboards.
  • Integrate and curate data from internal and external sources, and set best practices for analytics, reports, visualizations, and dashboards that explain results clearly to technical, non-technical, and senior audiences.
  • Work with stakeholders across the company to understand their needs and turn that understanding into analytics that shape strategy and performance; guide business leaders with confidence in the analysis so execution stays smooth.

Desired Qualifications

  • Experience with cloud-based Big Data, machine learning, and analytics technologies such as Databricks.
  • Experience with LLMs, prompting, or agentic and generative AI workflows.

About the Company

Hertz

Car rental services and fleet management

Hertz rents cars, trucks, and vans to leisure and business customers through a global network of airport and urban locations. Customers choose a vehicle, set dates and pickup location, and pay the rental fee plus optional extras like insurance or GPS. The company differentiates itself with broad accessibility, convenient airport and city concessions, flexible pricing, and value-added add-ons. Its goal is to provide easy, reliable mobility for individuals and fleets by offering broad access, clear pricing, and useful services.

Company size
10,001+
Company stage
IPO
Headquarters
Shadow Wood, Florida
Founded
1918

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