Senior Data Scientist, ML & Forecasting for Damage Tech

Hertz; Estero (FL); On-site; USD 95,000 - 116,000; Full time

Benefits offered by this job

40% Hertz rental off

Paid Time Off

Medical, Dental & Vision

401(k) matching

Parental Leave

Employee Assistance Program

Educational Reimbursement

Discounts

Job summary

Hertz is seeking a Senior Data Scientist to join the Damage Science Team in the US. The role focuses on building and deploying predictive, descriptive, and prescriptive models to optimize damage management and maintenance decisions, with projects involving LLMs, forecasting repair needs, optimization of disposition, and demand planning.

Ideal candidates have 5+ years in data science, strong SQL/Python, end-to-end ML experience, and a degree in CS or a quantitative field; prior experience in car

Qualifications

• 5 years hands-on experience in a data scientist role.
• 3+ years of SQL and Python experience.
• 3+ years end-to-end ML model development.
• Demonstrated experience using machine learning to drive a business impact.
• Experience in a ML or data scientist role with car rental or technology company.
• Bachelor or Masters degree in Computer Science, or other quantitative discipline such as statistics, mathematics, physics or engineering.

Responsibilities

• Formulate the model development lifecycle end-to-end (problem statement to deployment).
• Build and maintain descriptive, predictive, and prescriptive models to measure product/service performance.
• Define and implement analytics, reports, visualizations, and dashboards for technical and non-technical audiences.
• Build partnerships across functions to identify use cases and drive business value via OKRs.
• Drive business impact with an owner mentality, supporting pipeline creation or decision-support analytics.

Education

CS or quantitative degree

Tools

SQL

Python

ML modeling

Job description

Hertz is seeking a Senior Data Scientist to join the Damage Science Team in the US. The role focuses on building and deploying predictive, descriptive, and prescriptive models to optimize damage management and maintenance decisions, with projects involving LLMs, forecasting repair needs, optimization of disposition, and demand planning.

Ideal candidates have 5+ years in data science, strong SQL/Python, end-to-end ML experience, and a degree in CS or a quantitative field; prior experience in car