PhD - Gamification & Behavioral Systems

hace 2 semanas

Madrid, Madrid, España Silk A tiempo completo

About Silk

Silk is building Europe's leading hyperlocal rewards network, connecting people with the neighborhoods they live in and the local businesses they care about.

We turn everyday, real-world spending into rewards — automatically, without coupons, cards, or friction. Our product blends payments data, open banking, and behavioral design to create daily engagement at scale.

We are now looking for a PhD-level to help us design and optimize the gamification and incentive systems at the core of Silk.

The Role

You will lead the design and experimentation of AI-driven gamification systems that influence real-world behavior: where people shop, how often they return, how they explore neighborhoods, and how communities grow.

This is not a theoretical role. Your work will directly shape a live product used in physical stores, streets, and neighborhoods.

You will work closely with the CEO, CTO, product, and design teams.

  • What You'll Work On
    Design and optimize gamification mechanics (challenges, rewards, progression, randomness, social dynamics).
  • Apply reinforcement learning, bandits, causal inference, and behavioral modeling to real user behavior.
  • Personalize incentives and rewards in real time based on user patterns and context.
  • Balance short-term engagement with long-term retention and economic sustainability.
  • Experiment with neighborhood-level dynamics (collective challenges, social proof, local competition).
  • Define success metrics and run continuous experimentation (A/B tests, simulations, offline modeling).

  • Translate academic concepts into systems that actually ship.

  • What We're Looking For
    PhD in Computer Science, AI, Machine Learning, Computational Social Science, Behavioral Economics, or a related field.

  • Strong background in applied machine learning, not just theory.
  • Experience with:
  • Reinforcement learning or decision-making under uncertainty
  • Optimization of incentive systems
  • User behavior modeling or recommender systems
  • Comfort working with imperfect, real-world data.
  • Ability to explain complex ideas in simple terms.
  • Product mindset: you care about impact, not just papers.

Bonus points if you've worked on:

  • Gamification systems
  • Marketplaces or two-sided networks
  • Consumer apps with daily engagement

  • Behavioral or experimental economics

  • What This Is
    Not
    Not a pure research lab role

  • Not a hype-driven "AI for AI's sake" position
  • Not a corporate environment

This is applied, messy, human, and real.

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