Looking for a enior Python quant/quantitative engineer We’re looking for someone who can: - design probabilistic pricing models for fixed-odds prediction markets (politics, sports, macro, entertainment, etc.); - implement live odds updates based on order flow and external data; - define basic risk management and exposure controls (limits, auto-adjustment of odds, scenario checks); - run simulations and backtests to evaluate and improve the models; - deliver a production-ready Python implementation that our engineering team can integrate into our backend; For this role we specifically need someone with excellent Python skills – that is the primary and non-negotiable tech stack for the modelling and testing work. In addition, it would be a strong plus if they also have experience with Golang, as our backend is built in Golang and there may be some integration and collaboration with our engineering team. The core of our pricing and risk algorithm is already implemented. What we mainly need support with now is: - testing and validating the existing models; - backtesting and stress testing under different scenarios; - identifying weaknesses or edge cases; - recommending improvements and, where needed, refining the implementation in Python and aligning it with our Golang backend;