As the Data Science Manager, you will oversee a team focused on ensuring the pricing model remains accurate, reliable, and continuously optimized and aligned with business goals
Continuous Model Retraining:
Maintain agility by retraining models to quickly reflect market and competitive dynamics
Cross-Functional Collaboration:
Act as the primary liaison between data science, engineering, and business teams to align pricing strategies with organizational goals.
A/B Testing of Pricing Strategies:
Design and execute experiments to evaluate and improve pricing strategies
Model Monitoring & Reliability:
Ensure all business processes dependent on the pricing model run smoothly, with proactive monitoring and issue resolution.
Incident Management & Risk Mitigation:
Establish protocols for rapid response to model failures or anomalies to minimize business impact
Talent Development:
Mentor team members, foster a culture of learning, and support career growth within the team.
Strong background in data science, machine learning, or applied statistics, ideally with experience in pricing or revenue optimization for B2B businesses.
Proven ability to work in complex, general environments and manage operational processes for ML systems.
Leadership experience:
Previous people management experience is a plus, but not mandatory. We welcome candidates who have served as team leads and are ready to transition into a full managerial role. Excellent communication and stakeholder management skills. Strong software engineering background, with proven experience in productionizing and scaling global ML models. Experience with ML model lifecycle management (training, deployment, monitoring). Familiarity with A/B testing frameworks and experimental design.