If you're looking for a data-focused job in an investment bank, you don't have to be a data scientist or a quant. Newer roles are emerging: you could be a data strategist.
In the past, finding data was an easy task, simply because there was less of it available. In recent years, with the advent of alternative data, the number of datasets has mushroomed. According to Neudata, there are now over 1000 alternative datasets, compared to under 300, a decade ago. These datasets can range from satellite images to social media and more.
What does the data strategist do?
The data strategist role is all about managing the complexity of finding these new datasets.
Where do data strategists work?
It is no longer the case that alternative datasets are purely the realm of firms like Renaissance Technologies. Many funds are increasingly trying to tap into these unusual datasets to find signals to trade the market, with techniques which include machine learning. As a result, today, there are data strategists, not only in the largest quant hedge funds, but also in many discretionary funds too, given the increased demand for alternative data, in particular following COVID-19.
Data strategists and the procurement process
Data strategists manage the whole process of sourcing alternative datasets, often working closely with quants, data scientists and portfolio managers. They help to screen datasets to select those which are likely to show promise and fit the requirements of the business. Quants and data scientists then test these shortlisted datasets in a rigorous process. If a dataset passes this testing stage, data strategists will also negotiate the price with the data vendor. Only a small number of datasets make through this this final stage.
How do data strategists find the datasets?
It is possible to learn about many datasets from alternative data aggregators such as Neudata or Eagle Alpha, which list many datasets and vendors on their platforms. Alternative data conferences can be a good place to meet data vendors and to network with other data strategists.
However, many datasets can be elusive, and it is these datasets that may be of particular interest for funds. If fewer investors are using signals from a particular dataset, it is likely to suffer from a slower rate of alpha decay. Data strategists are often in a race to find the most exciting datasets, before they become mainstream.
It requires a lot of work to find these more unusual datasets. In some cases, data strategists might even approach data owners who have no idea about the value of their data, and help them create a data product. Indeed, there are a number of datasets which have come to market in this way.
What skills do you need to be a successful data strategist?
Data strategists need the technical skills to understand data. It isn’t necessarily about coding lots of Python every day or discussing the minutiae of a particular regression technique. Instead, it’s more about having the intuition to know which datasets are likely to be valuable for the firm’s trading style and to leave those which are likely irrelevant. Data strategists also need excellent soft skills, given that a data strategist acts as a bridge between the outside firms and internal clients such as data scientists and portfolio managers.
Saeed Amen is a systematic FX trader, running a proprietary trading book trading liquid G10 FX, since 2013. He developed systematic trading strategies at major investment banks including Lehman Brothers and Nomura, and runs Cuemacro, a consulting and research firm focused on systematic trading.
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