A Day in the Life:

We are seeking a highly skilled and motivated Order to Cash Data Scientist to join our finance team. The ideal candidate will leverage advanced data analytics, and statistical techniques to analyze billing and chargeback traffic by brand to offer insights to the business as well as optimize our accounts receivable processes, enhance cash flow forecasting, and ultimately reduce bad debt. This role requires a deep understanding of data science methodologies, financial principles, and excellent problem-solving skills. 

The starting salary for this role is $85,000. 

What You’ll Do:

Data Analysis and Modeling

• Analyze billing and chargeback traffic data to identify trends, patterns, and anomalies.
• Develop predictive models to forecast cash collections, customer payment behaviors, and bad debt risks.
• Utilize machine learning algorithms to enhance accuracy in receivables predictions and risk assessments.

Process Optimization:

• Identify inefficiencies in current receivables processes and propose data-driven solutions.
• Collaborate with the finance team to implement automation and process improvements.
• Monitor and evaluate the effectiveness of implemented strategies and adjust models as necessary.

Reporting and Visualization:

• Design and maintain dashboards and reports to communicate key metrics and insights to stakeholders.
• Provide actionable recommendations based on data analysis to support strategic decision-making.
• Present findings to senior management in a clear and concise manner.

Data Management:

• Ensure data integrity and accuracy by developing and maintaining data quality standards.
• Collaborate with IT and data engineering teams to enhance data collection and storage systems.
• Implement data governance best practices to manage sensitive financial information securely.

Cross-Functional Collaboration:

• Work closely with finance, accounting, operations, and sales teams to understand business needs and align data science initiatives with organizational goals.
• Act as a subject matter expert on data analytics within the receivable’s domain.

What We’re Looking For:

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Finance, or a related field. Advanced degrees are a plus.
• Ideally 3+ years of experience in data science or analytics roles, preferably within the finance or accounting sectors.
• Proven track record of developing and deploying predictive models and machine learning algorithms.
• Proficiency in programming languages such as Python, R, or SQL beneficial.
• Experience with data visualization tools like Alteryx,Tableau, Power BI, or similar.
• Familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, Keras) and statistical software beneficial.
• Strong analytical and problem-solving abilities.
• Excellent communication and presentation skills.
• Ability to work independently and as part of a team in a fast-paced environment.

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

The Hertz Corporation operates the Hertz, Dollar Car Rental, Thrifty Car Rental brands in approximately 9,700 corporate and franchisee locations throughout North America, Europe, The Caribbean, Latin America, Africa, the Middle East, Asia, Australia and New Zealand. The Hertz Corporation is one of the largest worldwide airport general use vehicle rental companies, and the Hertz brand is one of the most recognized in the world.   US EEO STATEMENT  At Hertz, we champion and celebrate a culture of diversity and inclusion. We take affirmative steps to promote employment and advancement opportunities. The endless variety of perspectives, experiences, skills and talents that our employees invest in their work every day represent a significant part of our culture – and our success and reputation as a company.  Individuals are encouraged to apply for positions because of the characteristics that make them unique.  EOE, including disability/veteran