About Smarkets

The Smarkets exchange is a multi-billion pound trading platform with a rapidly growing ecosystem of sophisticated users who apply financial trading techniques to the world of betting. We’re looking for a Senior Quant Analyst to join our Quant Group to provide valuable, data-driven insights to illuminate the underlying realities of our trading domain.

We’re big on continuous improvement at Smarkets, and so a large component of your role will be to analyse the results of sporting events and make actionable recommendations for what we can do differently next time. Having generated terabytes of data from multiple sources in an interesting and challenging domain, we are now applying this data to more and more complex research and can offer you the opportunity to work on a wide range of problems in this world.

Responsibilities

We are looking for a quant strategist who has some experiences in developing market making strategies on financial markets or betting exchanges. The candidate will be involved in the full development cycle of the strategies.

Requirements

  • Master or PhD Degree in a relatable subject such as mathematics, physics, statistics, machine learning...
  • 2 years or more experience in market making/liquidity provisioning
  • Solid knowledge in statistics, econometrics or statistical learning
  • Strong coding, being able to write efficient and performant code
  • Capable of modelling liquidity, price and risk across correlated contracts
  • Experience in building trading signals on trend, counterparties, order book …
  • Experience in working with large datasets and statistical and numerical programming packages in Python
  • Database querying knowledge (PostgreSQL)

Desirable attributes

  • Experience in executing in limit orders across markets
  • Good knowledge of machine learning, experience with Python packages such as Keras and Scikit-Learn
  • Derivative trading, understand the risk sensitivity to a parameter of a pricing model and being able to build a strategy that cover this risk across markets.
  • Experience in building Reinforcement Learning algorithm in continuous action space

Perks

  • Self-management structure similar to Valve
  • Set-your-own-salary and unlimited holiday policies
  • Flexible and collaborative work environment
  • Daily catered meals (breakfast, lunch and dinner), free drinks and food all day, parties on a frequent basis
  • Work with one of Europe’s smartest workforces

Compensation Guidance

Initial salary will be determined by peer review from candidate profile, experience, market rate and interview performance. After 6 months in the company, employees will be able to participate in our set-your-own-salary process.This is a full-time job based at our office in Tower Hill, London.

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