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Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. The company's core product is the Market Model—a proprietary AI-powered system delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture using market data with full transparency, it has been deployed in global aviation and scales across volatile markets, delivering an average profit uplift of 7% for corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul.
The Price Optimization (PO) team is the decision-making engine. The team works with large-scale customer data and market predictions—such as demand forecasts—to drive revenue management decisions. Core responsibilities include designing data pipelines that ingest customer data, running it through an optimization engine that simulates the market (weighing competition, pricing constraints, inventory availability, predictive models, and client business policies), and generating price recommendations. Quality, reliability, and attention to detail are critical before recommendations reach clients.
As Algorithm Team Lead - Optimization, you will lead the team through architecture decisions, development, and deployment of mission-critical systems while growing and mentoring a high-performing team.
Key Responsibilities:
- Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure
- Design, build, and maintain distributed data processing workflows (batch and streaming)
- Drive best practices for data quality, validation, testing, and observability
- Own and evolve Fetcherr's data architecture in alignment with business and product goals
- Manage sprint planning, task breakdown, code reviews, and performance feedback for your team
- Contribute hands-on to key development tasks and architecture decisions
- Recruit, mentor, and grow the data science engineering team
Requirements:
The posting does not explicitly state years of experience, required skills, education, or certifications. However, the role implies strong expertise in distributed data systems, machine learning infrastructure, data pipeline design, team leadership, and hands-on technical contribution.
