Multi-asset online brokerage for forex, CFDs, indices, commodities, and crypto
ThinkMarkets operates a global multi-asset brokerage built on C++ infrastructure (C++17/C++20, WebSocket, CMake) paired with MetaTrader 4 and cTrader trading engines. Hiring is heavily skewed toward marketing (6 roles) and sales (3) versus engineering (1), reflecting a growth-and-distribution phase — the project roster confirms this: paid acquisition campaigns, attribution modeling, partner activation, and audience segmentation dominate their roadmap. Core pain points cluster around acquisition efficiency (CAC/LTV, paid campaign optimization) and attribution accuracy, suggesting they're scaling customer acquisition faster than measurement keeps pace.
Notable leadership hires: Head of Partnerships
ThinkMarkets is a London-founded (2010) online brokerage operating globally under multiple regulatory licenses. The company offers trading across forex, CFDs, indices, commodities, equities, futures, and cryptocurrency via its proprietary ThinkTrader platform. The product is sold primarily through direct marketing channels and a partner network. Active hiring spans the US, UK, and UAE, with emphasis on marketing, sales, and partnership roles. The tech stack reflects a trading-platform operation: low-latency C++ execution infrastructure, Salesforce CRM, and heavy reliance on Google and Meta for paid acquisition.
ThinkMarkets runs C++17/C++20 backend services on Unix with WebSocket for real-time data, MetaTrader 4 and cTrader as trading engines, Salesforce for CRM, and Mixpanel for product analytics. Marketing stack includes Google Analytics 4, Meta Pixel, Looker Studio, and DV360.
Primary focus areas are mobile app growth, multi-market paid acquisition campaigns, attribution model development, partner activation and onboarding, and customer journey optimization. Projects emphasize paid media across SEM and mobile app marketing for FX and CFD products.
ThinkMarkets's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.