Job Title: Lead Data Scientist – Revenue Optimization & Pricing

Location: Remote

Compensation: $90–$100 hourly

Job Type: Long Term Contract

Job Summary

We are seeking a Lead Data Scientist to support strategic pricing and revenue optimization initiatives within the onboard revenue organization. This role combines machine learning, operations research, and optimization techniques to drive pricing decisions and maximize revenue outcomes. The ideal candidate will not only build predictive models but also leverage model outputs to develop optimization strategies and prescriptive recommendations that directly influence business decisions. This position requires an individual capable of independently solving complex analytical problems and owning projects from conception through implementation.

Key Responsibilities

• Develop machine learning models to support pricing and revenue management initiatives.
• Apply optimization and operations research methodologies to business challenges.
• Build prescriptive analytics solutions that translate model outputs into actionable recommendations.
• Design and implement mathematical optimization frameworks for pricing strategies.
• Partner with business stakeholders to solve complex revenue optimization problems.
• Work with large-scale datasets using distributed computing technologies.
• Lead analytical initiatives from discovery through deployment with minimal oversight.
• Deliver measurable business impact through data-driven decision making.

Required Qualifications

• 7+ years of Data Science experience.
• Strong proficiency in Python.
• Experience developing and deploying machine learning models.
• Experience working with Big Data technologies and large datasets.
• Hands-on experience with PySpark.
• Proven experience with pricing, revenue optimization, or prescriptive analytics projects.
• Strong problem-solving skills with the ability to independently lead complex initiatives.
• Experience translating analytical findings into business recommendations.

Preferred Qualifications

• Background in Operations Research, Optimization, or Decision Science.
• Experience with optimization techniques such as:
  • Mathematical Optimization
  • Dynamic Programming
  • Prescriptive Modeling
• Experience with optimization libraries such as:
  • SciPy
  • GEKKO
  • Similar optimization frameworks
• Industry experience in:
  • Airlines
  • Hospitality
  • Hotels
  • Travel
  • Revenue Management organizations
• Experience delivering measurable revenue impact through pricing and optimization solutions.
• Advanced degree in Data Science, Statistics, Operations Research, Mathematics, Engineering, or a related field.

EEO: We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital status, military or veteran status, citizenship, pregnancy (including childbirth, lactation, and related conditions), or any other protected status in accordance with applicable federal, state, and local laws.

Benefits & Perks: Brooksource offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employee’s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc.

Pay Disclaimer: The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.