Sr Data Scientist - Commercial

On-siteSeniorData Scientistposted 2mo ago

✦Role summaryAI-generated

This Sr. Data Scientist role at Hertz focuses on designing proprietary revenue optimization tools using advanced ML techniques like reinforcement learning and time-series forecasting to enhance commercial offers. The position requires cross-functional collaboration with business teams to prototype and deploy end-to-end solutions that drive measurable revenue growth.

Skills required

Time series forecasting Reinforcement learning Optimization modeling Large scale data analysis Python r SQL Machine learning Data pipelines Stakeholder collaboration Business insight delivery Time series Data analytics Statistics Data science Python R SAS C++

About this role

Hertz Revenue Management is seeking a highly motivated, intellectually curious, and talented Sr. Data Scientist to join a team that is responsible for optimizing Hertz's revenue offers. The Sr. Data Scientist will collaborate on designing, delivering, and maintaining proprietary optimization products that result in improved customer offers and increased revenue for Hertz. The role partners across Revenue Management, Pricing, Sales, Product, Distribution, Operations Research, IT, and vendors to identify opportunities, define requirements, provide insights, prototype products, and deliver end-to-end solutions

What You’ll Do:

Identify commercial opportunities to optimize Hertz revenue that can be addressed by developing data sources, methods, tools and models, including time series forecasting, reinforcement learning, or optimization modeling
Enhance existing analytical tools and develop new solutions/tools based on large data sets
Own and deliver end-to-end solutions, including coordination with stakeholders and IT, implementation, and support
Promote the long-term customer vision that supports Hertz's business strategy as the marketplace evolves, and new products are introduced
Actively develop close relationships and coordinate with commercial business units, Operations Research, Finance, IT and senior management to ensure timely execution of Hertz Revenue Management sponsored projects
Maintain a pulse on industry efforts, disruptive technologies, and champion solutions to further Hertz's position as industry leader
Balance multiple priorities in a fast-paced environment
Understand the interrelationships between Fleet, Pricing, and Revenue Management, and the combined impact on the Hertz Customer experience
Developing the Data Analytics Team
Other duties and tasks as assigned

What We’re Looking For:

Master’s degree in operations research, statistics, computer science, or a related quantitative field required.
2-5 years of industry experience in modeling, data science or operations research required.
Highly proficient communication skills and ability to actively advocate for Hertz Revenue Management solutions across the enterprise
Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/optimization software (e.g. R, SAS, Gurobi, C++, etc.) required.
Experience with big data: processing, filtering, and presenting large quantities of data required.
Ability to understand and work with large, unstructured data sets
Proven success in solving complex quantitative problems
Must be able to work well with diverse groups in a time-sensitive team environment with minimal supervision, be results oriented and able to meet or exceed deadlines with attention to detail and follow through
Demonstrated ability to handle multiple projects through to solution delivery
Consistently prioritizes safety and security of self, others, and personal data.
Embraces diverse people, thinking, and styles.

Preferred Qualifications:

5+ years in operations research, statistics, computer science, or related science field.
Experience with time series forecasting, reinforcement learning, machine learning, or optimization.
Knowledge of revenue management theory or travel industry systems/data

The starting salary for this role is $105K; commensurate with experience.

What You’ll Get: