Lead Applied Scientist

• Lead explanation, configuration, validation, and best-practice adoption of PROS AI solutions during sales engagements, customer implementations, and strategic initiatives
• Collaborate with Research Science, Machine Learning Engineering, Professional Services, Sales, and Product Management teams
• Validate and operationalize research outcomes by assessing model performance, business impact, usability, robustness, and customer adoption
• Act as scientific lead for high-impact sales and implementation engagements
• Guide customers and internal stakeholders on configuring and applying PROS AI solutions
• Communicate complex machine learning, optimization, forecasting, pricing, and revenue management concepts to technical and non-technical audiences
• Address advanced customer questions about solution design, methodology, model outputs, and business impact
• Perform advanced analyses across multiple PROS AI solutions to identify customer value opportunities
• Recommend solution configurations tailored to customer objectives and industry use cases
• Develop analytical frameworks, dashboards, and tools supporting implementation, adoption, and business decision-making
• Validate solution behavior, explain results, and ensure scientific rigor throughout implementations
• Partner with Research Scientists and Machine Learning Engineers to refine solutions and influence future science capabilities
• Translate customer challenges into actionable product and science enhancements
• Help define training programs, implementation methodologies, and best practices for broader self-service adoption
• Provide mentorship in the AI Research team and scientific guidance across the organization
• Contribute to thought leadership through presentations, blogs, training materials, webinars, conferences, and industry events
• Represent PROS at customer-facing events and strategic industry engagements
• Drive improvements that reduce implementation effort, shorten time-to-value, and improve customer outcomes

• Master's degree in Operations Research, Data Science, Machine Learning, Statistics, Applied Mathematics, Computer Science, Industrial Engineering, or related quantitative field
• 10+ years of experience in pricing, revenue management, forecasting, optimization, machine learning, offer optimization, or related decision science disciplines
• Expertise in statistical modeling, machine learning, and applied AI techniques
• Strong proficiency in Python, SQL, and Databricks
• Experience working directly with customers, implementations, or consulting engagements
• Strong presentation, communication, and stakeholder management skills
• Ability to explain advanced scientific concepts to technical and executive audiences
• Demonstrated ability to influence cross-functional teams and strategic decision-making
• Experience with pricing, revenue management, forecasting, recommendation systems, or offer optimization
• Experience with multiple AI solution areas such as forecasting, optimization, machine learning, and generative AI
• Familiarity with reinforcement learning, recommendation systems, LLM applications, or agentic AI workflows
• Experience working in enterprise software
• Experience developing analytical dashboards and visualizations using Power BI, Tableau, or Databricks
• Previous consulting, implementation, customer-success, solution architecture, or technical advisory experience
• Demonstrated thought leadership through conference presentations, publications, blogs, training programs, or industry engagement

• Flexible ways of working
• Continuous learning
• Opportunities to grow, innovate, and develop professionally
• Customer success-focused culture
• Supportive workplace culture