Quantitative Researcher (Prediction Markets)

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Only applications here are reviewed: https://jobs.deel.com/8d80a7ac-56ca-4e5f-87d0-f106ddc5a243/job-details/75484e74-324d-4db0-a693-9de3f6b7de33

Introduction

OpenForage (https://openforage.ai) delivers institutional yields by monetizing strategies submitted by agents. We going to build the best platform for organizing agent labour to bet on the long tail of emergent intelligence and believe that whomever can control the swarm will play an important role in the future.

We are looking to hire a Quantitative researcher with a focus on developing alpha signals in prediction markets in a market-neutral manner. We love to work with people with an insatiable appetite for winning, are highly autonomous, innately curious, self-driven, self-motivated and derive great pleasure in accomplishing extremely difficult goals. For now, we are only looking for candidates in Singapore or are willing to relocate to Singapore.

Hiring Process

Our hiring process is straightforward, unpretentious and tilts towards empirical excellence. It consists of two rounds:

1. A take-home project where you can independently solve a closed problem where we can score the goodness of the solution and

2. A sit-in project where we can simulate real working conditions by solving an ambitious, difficult open problem together.

The take-home project is open to everybody, and you can find it here: https://github.com/systematic-long-short/polymarket-btc-takehome. We will contact the candidates that have done well for the take-home project to work on the sit-in project. Via the process of the sit-in project we will learn what it's like to work together and if we are a good fit for each other. Right after it concludes, we will provide resolution within 3 days. The sit-in project for this role will be designing an algorithm that clusters prediction market markets and events in real-time such that prices in each cluster have maximal co-movement.

Objectives

1. Conduct research on developing market-neutral alpha signals in prediction markets such as Polymarket.

2. Build trading strategies that systematically exploit statistical mispricings across prediction markets.

3. Build and maintain infrastructure required to execute on prediction markets, e.g. real-time data pipelines, order management.

4. Wield the many and varied responsibilities and hats needed to succeed and do world-class work.

Qualifications

1. An extreme dogged determination to succeed and do something meaningful in life.

2. Demonstrate deep practical knowledge in modern deep learning architectures and fuzzy optimisation.

3. Demonstrate deep practical knowledge in working with large, messy, unstructured datasets.

4. Take an AI-first approach to solve problems with an intent on achieving unprecedented talent leverage.

Compensation & Perks

1. Competitive base salary and an eat-what-you-kill attribution to protocol revenue.

2. Radical responsibility and autonomy in a no bullshit environment with an emphasis on urgency.

3. Ownership of the protocol.