Lead Applied Researcher — Dynamic Pricing

inDrive; Greater London; On-site; GBP 110,000 - 160,000; Full time

Job summary

inDrive seeks a Lead Applied Researcher to advance dynamic pricing in our London team. You will design and deploy real-time pricing policies, frame pricing under uncertainty, and collaborate with engineering to scale models.

You will drive experiments, monitor performance, and contribute to methodological choices. This role offers international exposure and the chance to impact pricing across 1100+ cities.

Qualifications

• Experience in data science, applied research or pricing optimization.
• Strong background in statistics and optimization.
• Ability to translate problems into production solutions.
• Experience with production ML systems.

Responsibilities

• Design and improve dynamic pricing policies using elasticity and demand-supply modeling.
• Frame pricing as a decision problem under uncertainty and delayed feedback.
• Develop, test, and deploy a real-time pricing algorithm.
• Design and analyze A/B experiments to evaluate pricing impact.
• Productionize models with engineering for scalability and robustness.
• Monitor system performance, stability, and long-term effects.
• Contribute to methodological choices in optimization and reinforcement learning approaches.

Skills

Data science experience

Statistics and optimization

Production-grade solutions

Python and SQL

Tools

Python

SQL

Job description

Put your data science role in front of the right audience - Post your job

Lead Applied Researcher - Dynamic Pricing

Organisation inDrive

Locations London, UK

Application Deadline 30 days remaining

Key Responsibilities

• Design and improve dynamic pricing policies, including elasticity and supply/demand response modeling
• Frame pricing as a decision system under uncertainty and delayed feedback
• Develop, test, and deploy a real-time pricing algorithm
• Design and analyze A/B experiments to evaluate pricing impact
• Productionize models in collaboration with engineering, ensuring scalability and robustness
• Monitor system performance, including stability, feedback effects, and long-term behavior
• Contribute to methodological choices (e.g., optimization, control, reinforcement learning-inspired approaches)

Skills, Knowledge and Expertise

• Professional experience in Data Science, Applied Research, or algorithmic product optimization, preferably in marketplaces or pricing systems
• Strong background in statistics, optimization, and causal inference
• Proven ability to move from problem formulation to production-grade solution
• Proficiency in Python, SQL, and experience with production ML systems

Nice to Have

• Experience with economic modeling (elasticity, auctions, policy design)
• Familiarity with control systems, reinforcement learning, or online optimization
• Experience working with real-time, high-load systems
• Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 47 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.