Max Pagels

I enjoy tackling hard machine learning problems with unconventional solutions, driven by the field's blend of theory and empirical progress and a healthy frustration with convention. I maintain Formative (a quantitative reasoning library) and Gittins (production-grade bandits).

If you are interested in the unconventional, and are willing to accept failure in the pursuit of something genuinely innovative, please be in touch.

max.pagels@protonmail.comGitHubLinkedIn

Career

  1. 2026–Member of Technical Staff, Qutwo
  2. 2023–26Head of Technology, Marimekko
  3. 2021–23Head of Technology, Fourkind / Thoughtworks
  4. 2017–21Machine Learning Partner, Fourkind
  5. 2015–17Developer → Data Science Specialist, SC5 / Nordcloud

Selected work

Contextual bandits & real-time optimisation

Built some of the first real-time contextual bandit systems for high-volume recommendations in the Nordics, and real-time webpage optimisation for fashion retail. Constraints: per-observation online updates, partial (bandit) feedback, non-stationary reward distributions, and serving inside sub-second request budgets. Evaluation done off-policy (IPS / doubly-robust) rather than on live traffic where experimentation was constrained.

Bidding under partial information

Bidding algorithms for second-price advertisement auctions under partial information, allocating ten-digit (€1B+) annual media budgets. Constraints: censored feedback from lost auctions, budget pacing, and non-stationary competition.

Causal estimation of bonus program retention

Estimated the causal impact on retention of a third-party bonus/loyalty program carrying eight-digit (€10M+) annual license fees, to decide whether the spend was actually driving incremental behaviour. Constraints: no clean randomised holdout, confounding from self-selecting engaged users, and a decision that had to withstand scrutiny. Used instrumental-variable regression and difference-in-differences to isolate the effect; the incremental retention did not justify the fees, and the program was decommissioned, saving €10M+ annually.

High-availability payments infrastructure

Implemented payment processing (charges, holds, automatic refunds) and high-availability hosting for retail with multi-million annual revenues, alongside event-driven backends and a storefront for personalised fashion.

Global commerce replatforming

Architected and shipped a composable, event-driven commerce platform for global fashion retail: headless CMS, commerce engine, payments, tax, and personalisation services, replacing a monolithic platform that couldn't absorb traffic spikes or multi-channel content reuse. Constraints: zero-downtime migration of a live revenue stream, multi-market catalogues, pricing and tax, and content authored once but published across web, email, SMS, and B2C channels.

Clients

Veikkaus, Elisa, Sanoma Media, Wayfair, and Hennes & Mauritz.

Education

MSc, Computer Science, University of Helsinki; major in software systems, extended minor in mathematics and statistics. Natively trilingual (Swedish, Finnish, English).

Service

Finnish Defence Forces, active reservist.

Writing & talks

  • Off-policy Estimation in the Agentic Era — 2026, PDF
  • On Prompting, Priors, and What It Takes for LLMs to Produce Novelty — 2026, PDF
  • Machine Learning Reductions & Mother Algorithms, Part I: Introduction — Medium
  • Machine Learning Reductions & Mother Algorithms, Part II: Multiclass to Binary Classification — Medium
  • Real-World Reinforcement Learning — Slides
  • Improving the Delivery Cycle: A Multiple-Case Study of the Toolchains in Finnish Software Intensive Enterprises — IST, 2016
  • The Highways and Country Roads to Continuous Deployment — IEEE Software, 2015
  • A Behavior Marker tool for measurement of the Non-Technical Skills of Software Professionals: An Empirical Investigation — SEKE, 2015
  • Examining the Structure of Lean and Agile Values Among Software Developers — XP, 2014