Senior Applied Researcher

Senior Applied Researcher will own well-defined marketplace efficiency problems end-to-end, from problem formalisation through modelling, deployment, and production monitoring. You will operate independently on complex problem areas, make explicit trade-offs between competing objectives, and partner closely with engineering to deliver robust, scalable solutions.

Key Responsibilities

• Conduct in-depth market research and analyze trends to identify opportunities for marketplace growth and optimization
• Develop and refine metrics, dashboards, and KPIs to monitor market performance and guide strategic decisions
• Generate and validate hypotheses to address key market challenges, presenting insights and actionable recommendations to stakeholders
• Investigate anomalies and deviations in key metrics, identifying root causes and proposing solutions
• Build predictive models and advanced analytics frameworks to forecast market trends and inform resource allocation

Skills, Knowledge and Expertise

• 4–7 years of industry experience in data analytics, data science, applied research, or PhD + 2–4 years post-PhD in industry
• End-to-end ownership of individual marketplace models, policies, or decision mechanisms
• Strong judgment in trading off model fidelity, latency, robustness, and business impact
• Proven ability to move from abstract problem formulation to production-grade decision logic
• Hands-on experience collaborating with engineering teams on deployment, iteration, and monitoring
• Demonstrated ability to reason about system behavior under uncertainty, delayed feedback, and partial observability
• Modeling supply-demand dynamics as stochastic, partially observed, feedback-driven systems; formalizing unit economics, service quality, and LTV as state variables and objectives
• Design and analysis of experiments under interference, spillovers, feedback loops, and adaptive policies (e.g., switchbacks, clustered interventions)
• Practical experience with DiD, panel methods, synthetic control, double-robust estimators, and causal ML approaches in production settings
• Ability to distinguish short-term experimental uplift from long-run equilibrium shifts and cumulative feedback effects using time-series and dynamic causal methods.

Why join us

• Help us challenge injustice by creating fair choices for millions of people across 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
• Annual salary from EUR 70 700 gross

Final benefits may vary depending on the location.