Sr Data Scientist - Fleet Planning
Estero, FL, United States
- Pay
Pay amount needs review — pay source
This role calls for strong technical grounding across data science, ML, and experimentation methods, including how to debug and validate them, and a bias toward using AI-assisted development workflows and emerging generative AI capabilities to accelerate delivery. You'll dig into what shapes fleet and product performance, partner with stakeholders across the business to turn that into decisions they can act on, and flag risks and opportunities early enough for leaders to act on them. The starting salary for this role is $110K, commensurate with experience. What You'll Do:
Read the full posting- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll bring
All qualificationsCore experience
- 5+ years of hands-on experience in a data science or data analytics role.
- Python & Frameworks: Strong Python skills and practical experience with common data science and ML libraries, such as pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow.
- 2+ years of intensive experience with cloud-based Big Data, ML, and analytics technologies, preferably Databricks.
- SQL & Visualization: Strong SQL skills with structured and semi-structured data, and experience with data visualization tools such as Tableau.
- Communication: Outstanding verbal, written, presentation, and facilitation skills, with the ability to explain technical and non-technical concepts across organization levels.
Preferred experience
- Experience with LLMs, prompting, or agentic/GenAI workflows is a plus.
Qualification wording
5+ years of hands-on experience in a data science or data analytics role.
Python & Frameworks: Strong Python skills and practical experience with common data science and ML libraries, such as pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow.
2+ years of intensive experience with cloud-based Big Data, ML, and analytics technologies, preferably Databricks.
SQL & Visualization: Strong SQL skills with structured and semi-structured data, and experience with data visualization tools such as Tableau.
Communication: Outstanding verbal, written, presentation, and facilitation skills, with the ability to explain technical and non-technical concepts across organization levels.
AI-Assisted Development: Practical experience using AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot, Databricks Genie) to accelerate coding, analysis, and documentation, plus the judgment to critically review, test, and harden AI-generated outputs. Experience with LLMs, prompting, or agentic/GenAI workflows is a plus.
Tools in this posting
- Python
- SQL
- Databricks
- NumPy
- pandas
- PyTorch
- Tableau
- scikit-learn
- TensorFlow
Source — Tool mentions in context
- ML & Modeling: Strong understanding of supervised and unsupervised learning, feature engineering, model selection, statistical evaluation, and the diagnosis of training, inference, and data-quality issues. - Python & Frameworks: Strong Python skills and practical experience with common data science and ML libraries, such as pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow. - AI-Assisted Development: Practical experience using AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot, Databricks Genie) to accelerate coding, analysis, and documentation, plus the judgment to critically review, test, and harden AI-generated outputs. Experience with LLMs, prompting, or agentic/GenAI workflows is a plus.
- Data Pipelines & Platforms: Experience with scalable data pipelines, cloud data platforms, and production or near-production analytical workflows. - SQL & Visualization: Strong SQL skills with structured and semi-structured data, and experience with data visualization tools such as Tableau. - Curiosity & Craft: A demonstrated interest in learning, testing, and responsibly applying emerging AI and data science capabilities.
- Simulation & Decisioning: 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/online evaluation. - AI-Assisted Development: Use approved AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot, Databricks Genie) to accelerate your own analysis, coding, testing, and documentation. Critically review, test, and harden AI-generated code and outputs for accuracy, security, reproducibility, and compliance with organizational standards. - Applied GenAI: Explore and prototype generative AI and agentic AI solutions where they fit the business problem: 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 any production use.
- 5+ years of hands-on experience in a data science or data analytics role. - 2+ years of intensive experience with cloud-based Big Data, ML, and analytics technologies, preferably Databricks. - A demonstrated record of delivering data science or ML solutions across multiple lifecycle stages: problem definition, data preparation, modeling, evaluation, implementation, and post-deployment performance assessment.
- Python & Frameworks: Strong Python skills and practical experience with common data science and ML libraries, such as pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow. - AI-Assisted Development: Practical experience using AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot, Databricks Genie) to accelerate coding, analysis, and documentation, plus the judgment to critically review, test, and harden AI-generated outputs. Experience with LLMs, prompting, or agentic/GenAI workflows is a plus. - Data Pipelines & Platforms: Experience with scalable data pipelines, cloud data platforms, and production or near-production analytical workflows.
Job description
A Day in the Life:
The Senior Data Scientist, Fleet Planning builds and ships the analytics, data science, and ML systems behind Hertz's fleet — from predictive and prescriptive models to the simulations, experiments, data pipelines, and dashboards that turn them into decisions and measurable business impact. You'll operate as a hands-on individual contributor, working closely with data engineers, analysts, software developers, and product managers to take that work from idea to production.
This role calls for strong technical grounding across data science, ML, and experimentation methods, including how to debug and validate them, and a bias toward using AI-assisted development workflows and emerging generative AI capabilities to accelerate delivery. You'll dig into what shapes fleet and product performance, partner with stakeholders across the business to turn that into decisions they can act on, and flag risks and opportunities early enough for leaders to act on them.
The starting salary for this role is $110K, commensurate with experience.
What You'll Do:
Problem Solving & Modeling: 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.
Solution Delivery: Own the end-to-end data science and ML lifecycle, from problem framing and feature engineering through experimentation, offline evaluation, production deployment, monitoring, and iteration based on real-world performance.
Simulation & Decisioning: 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/online evaluation.
AI-Assisted Development: Use approved AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot, Databricks Genie) to accelerate your own analysis, coding, testing, and documentation. Critically review, test, and harden AI-generated code and outputs for accuracy, security, reproducibility, and compliance with organizational standards.
Applied GenAI: Explore and prototype generative AI and agentic AI solutions where they fit the business problem: 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 any production use.
Metrics & Experimentation: Define success and performance metrics for current and new business initiatives, with particular focus on A/B tests.
Data Engineering: Design and maintain robust ETL processes that keep data accurate and accessible, and oversee the upkeep and optimization of existing pipelines and dashboards.
Reporting & Visualization: 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.
Stakeholder Partnership: 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 your analysis so execution stays smooth.
What We're Looking For:
Education: Bachelor's degree or higher in Computer Science, or another quantitative field such as statistics, mathematics, physics, or engineering.
Experience:
5+ years of hands-on experience in a data science or data analytics role.
2+ years of intensive experience with cloud-based Big Data, ML, and analytics technologies, preferably Databricks.
A demonstrated record of delivering data science or ML solutions across multiple lifecycle stages: problem definition, data preparation, modeling, evaluation, implementation, and post-deployment performance assessment.
Technical Skills:
ML & Modeling: Strong understanding of supervised and unsupervised learning, feature engineering, model selection, statistical evaluation, and the diagnosis of training, inference, and data-quality issues.
Python & Frameworks: Strong Python skills and practical experience with common data science and ML libraries, such as pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow.
AI-Assisted Development: Practical experience using AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot, Databricks Genie) to accelerate coding, analysis, and documentation, plus the judgment to critically review, test, and harden AI-generated outputs. Experience with LLMs, prompting, or agentic/GenAI workflows is a plus.
Data Pipelines & Platforms: Experience with scalable data pipelines, cloud data platforms, and production or near-production analytical workflows.
SQL & Visualization: Strong SQL skills with structured and semi-structured data, and experience with data visualization tools such as Tableau.
Curiosity & Craft: A demonstrated interest in learning, testing, and responsibly applying emerging AI and data science capabilities.
Problem-Solving: A proven record of identifying and diagnosing problems and solving complex ones with simple, logical solutions.
Communication: Outstanding verbal, written, presentation, and facilitation skills, with the ability to explain technical and non-technical concepts across organization levels.
Collaboration: Strong interpersonal skills and a track record of building relationships across teams.
Adaptability & Agility: Comfortable operating in a fast-paced environment, managing ambiguity, and adjusting to changing priorities and technologies.
What You’ll Get:
Up to 40% off the base rate of any standard Hertz Rental
Paid Time Off
Medical, Dental & Vision plan options
Retirement programs, including 401(k) employer matching
Paid Parental Leave & Adoption Assistance
Employee Assistance Program for employees & family
Educational Reimbursement & Discounts
Voluntary Insurance Programs - Pet, Legal/Identity Theft, Critical Illness
Perks & Discounts –Theme Park Tickets, Gym Discounts & more
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on fa-evlf-saasfaprod1.fa.ocs.oraclecloud.com. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
This role calls for strong technical grounding across data science, ML, and experimentation methods, including how to debug and validate them, and a bias toward using AI-assisted development workflows and emerging generative AI capabilities to accelerate delivery. You'll dig into what shapes fleet and product performance, partner with stakeholders across the business to turn that into decisions they can act on, and flag risks and opportunities early enough for leaders to act on them. The starting salary for this role is $110K, commensurate with experience. What You'll Do:
- Location & working pattern
Estero, FL, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Oct 6, 2026
- Recorded sightings
- 19
- Last seen by us
- Oct 9, 2026
- Employer says posted
- Oct 1, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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