Senior Applied Scientist (Researcher) – Pricing

We are looking for an experienced Senior Applied Scientist (Matching) to design, develop, and optimize data-driven matching algorithms that efficiently connect riders with drivers and ensure a balanced, high-performance marketplace. In this role, you will work at the intersection of machine learning, applied mathematics, and marketplace economics, building scalable models that operate in real-time, adapt to dynamic supply and demand, and deliver measurable business impact. You will collaborate closely with product, engineering, and analytics teams to research, validate, and productionize advanced matching solutions. Key Responsibilities Design, develop, and improve matching and ranking algorithms that optimize marketplace efficiency, latency, and user experience Apply machine learning, statistical modeling, and discrete optimization techniques to real-time dispatching and matching problems Develop forecasting and behavioral models for supply, demand, and response dynamics that inform matching decisions Conduct advanced analytical research to identify inefficiencies and growth opportunities in existing matching logic Design and analyze A/B and S/B tests to validate algorithmic changes and quantify business impact Productionize models and analytical solutions in collaboration with engineers, ensuring scalability, reliability, and performance in high-load environments Build monitoring frameworks, metrics, and dashboards to track matching quality, marketplace balance, and model health Clearly communicate findings, trade-offs, and recommendations to technical and business stakeholders Skills, Knowledge and Expertise 4+ years of experience in data science, machine learning, or algorithmic research, preferably in marketplaces, matching, pricing, or dispatch systems Strong mathematical background, including probability theory, mathematical statistics, discrete optimization, and causal inference Solid understanding of marketplace dynamics, supply–demand balancing, and real-time decision systems Experience with tabular ML, ranking models, or recommendation/search-like problems Proficiency in Python and SQL, with hands-on experience processing large datasets and working with production ML pipelines Experience collaborating with engineering teams on deploying and maintaining models in high-load services Strong analytical mindset with the ability to balance deep research, practical constraints, and business impact Nice to Have Experience with auction mechanics, economic models, or incentive-aware matching Prior work on online optimization or real-time systems Familiarity with experiment design in large-scale marketplaces Why join us Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries Develop your professional skills with access to mentoring, career consulting, and learning programs Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects Work alongside people who take initiative, speak openly, and challenge themselves to grow Improve your language skills through co-financed courses and internal speaking clubs Final benefits may vary depending on the location.