Quantitative Trading is an extremely sophisticated area of finance that uses complex algorithms and advanced technology to discover actionable trends/patterns in financial data. Campbell North has experienced consultants who understand these complexities and can offer advice on all facets of a move or a hire.
Experienced quantitative trading professionals with full P&L responsibility
The difference between portfolio managers (PM's) and researchers is the responsibility for generating revenue. Quantitative PMs will either have a team of researchers working for them or be operating as a standalone unit in a larger firm. Leading a team you will have the ability and experience to identify an opportunity and then assemble a group around you that has the skills to take advantage of that. Standalone traders are normally highly skilled in research and development, but either have trades that do not scale beyond a certain point, or simply prefer working alone and/or have minimal interest in managing a team. Whatever your background we can advise on the best (and worst) firms to join for your individual needs.
A broad spectrum but for us it means those with at least 12 months industry experience
Quantitative researchers contribute to a collaborative trading book and are normally taking direction from someone more senior. Will have experience in either identifying trading signals or implementing trading strategies that can either add value to small trading groups or work collaboratively within larger research groups on broader research. We offer opportunities for experienced researchers who are looking to step up to running their own trading book or for people looking to join a firm/team that is better suited to their skills and career aspirations.
Phd level candidates with practical experience working with noisy, complex data
An entry level researcher will normally be completing a PhD or postdoctoral placement in an applied numerical subject (maths, computer science, physics, some areas of engineering). A strong command of key areas such as statistics (to make sense of the data sets), programming (to implement your ideas and transition concepts to a live algorithm) and prior experience of complex data analysis are all basic requirement. Problems are complex, results can be seen in real time and rewards are high which is why the best/brightest are consistently attracted to our clients. (for similar roles see our Data Science market)
From The Blog
Quant Trading Tech
If data is the fuel then technology is the engine driving quantitative trading. From cutting edge data analytics, simulation and trading platforms to real-time global feeds scraping petabytes of data from the market. All trading decisions are predetermined and fully automated from tick-to-trade with 100% reliance on elegantly crafted high performance systems.
Do you love solving problems using code? Perfect your skills working closely with experts in their field on a steep learning curve.
At the core of these firms are keen and highly skilled software engineers; those who love writing code and have put away the hours mastering their craft. Working at the heart of the technology infrastructure you will get to write code that will be deployed and have an immediate impact on the business. Regardless of your experience level you will make a difference from the outset and you will be treated as an intellectual equal.
Experienced programmers and experts in their field are always in demand to work on critical projects.
High profile projects require expertise and a track record in delivering automated trading technology with a high level of commercialism. Ideal for those with advanced knowledge and experience designing trading systems using major programming languages such as C++, Java or Python and the Linux operating system. Projects may range from building an entire trading platform for a start-up to rewriting order books, exchange connectivity or migrating to new scalable architecture.
Where technology meets research, here programmers with solid mathematics can build the tools need in quantitative research.
Often working very closely to quant traders and researchers in what is commonly called quantitative development designing and building research and trading tools. Projects can cover delivering simulation platforms, data analysis applications, machine learning tools, algorithm design and any other product that can help facilitate signal generation and strategy formation from raw data.