Have you noticed that Amazon has stopped providing purchase details in their order confirmation emails? As companies realize how valuable data is, they are becoming more protective of it. In Amazon’s case, they do not want third parties like Google or Microsoft scraping their emails to get insights into Amazon’s sales.

This was one of the anecdotes discussed earlier this year when CFA Society Toronto hosted a two-part webinar series entitled “Get Ready to Embrace Alternative Data.” Four presenters from different backgrounds delved into the rapidly growing industry surrounding alternative data. In this article, we cover some of the highlights from more than two hours of presentations, fireside chats, and question-and-answer sessions.

What is alternative data?

Alternative data is often described as anything that is not considered traditional data used by investors. Traditional data includes security prices, financial statement information, analyst estimates, and economic indicators. Alternative data is everything else.

Examples of alternative data include credit card transactions, email receipts, geolocation data, satellite images, app usage statistics, survey data, and social media posts. This data can range in complexity from highly structured numerical data (e.g., credit card transactions) to unstructured text, image, or video data.

A lot of alternative data is sourced from “exhaust data,” which refers to the huge amounts of data a primary business generates as a normal by-product of their operations. Credit card transaction data and geolocation information gathered by mobile phone apps are prime examples. Sometimes, the company that produces the alternative data may even overlook its value to investors or other users. Some vendors also originate alternative data, often by performing web scraping, polling, or some other data collection technique.

Why is alternative data gaining in popularity?

Presenter Adam Baron, a Director at Refinitiv who focuses on big data quantitative research, explained the growing popularity around alternative data: “Everyone is motivated by alpha and risk and looking for uncorrelated factors. There are also tonnes of academic papers and vendor studies that support the case for alternative data. And of course, there’s a fear of missing out.”

Finance professionals are always searching for new sources of information that could provide alpha and give them an edge over the competition. Better information may be provided by alternative data sources. For instance, consider credit card data that can track the sales of a publicly traded retailer. With advance knowledge of how the company is performing in a given fiscal quarter before the information is publicly disclosed during an earnings release, an alternative data analyst can trade on the information to capture alpha.

Presenter Abraham Thomas, Chief Data Officer at Quandl, cited the ongoing data explosion as a reason for alternative data’s growing popularity: “The amount of data being created and generated and then captured and used in the world is growing exponentially. Every company is a data company recording their own actions [and the actions of] their counterparties, their customers, [and] their competitors. There is no transaction anywhere in the world that doesn’t leave behind a footprint or a trail somewhere. And investors have realized that all of this information can be used to make better investment decisions.”

The industry and its players

Baron also spoke about the evolution of the industry, saying, “I think it’s more democratized now. A decade ago, it was the big well-funded hedge funds that had teams of data hunters, machine learning [and] artificial intelligence experts, and personnel that could do all the manual grunt work of mapping. And now there’s so much data out there in these marketplaces [that] whatever you’re looking for, you can search and probably find it. And with the advent of cloud technologies like Amazon Web Services (AWS) and Google Cloud Platform (GCP) and their machine learning frameworks, an individual can dabble in some stuff that [required the work of] teams of PhD’s in the past. I think mid to smaller players can really get into alternative data now.”

Thomas also talked about an entire ecosystem of other industry participants that fill various niches: “There are folks who are matchmakers between buyers and sellers, and they organize conferences or events, or publish data catalogues. There are companies that specialize in the technology of alternative data. Many of these datasets are big and quite messy, so there are firms that specialize in structuring, data engineering, and symbology, making sure data gets delivered on time. There are folks that focus on analysis, companies focused on data visualization, companies focused on data operations. There are lots of moving parts, and it’s a rich and thriving ecosystem.”

Careers in alternative data

As a relatively young and rapidly growing field, the alternative data industry offers many career opportunities. According to Thomas, “There are not enough people with the right skills and abilities to fill all the roles. And it’s ironic because firms are desperate for talent.”

Several presenters discussed the ideal qualities of the perfect candidate, which include a combination of domain expertise, a broad set of technical skills, and the ability to communicate. However, everyone acknowledged that these candidates are extremely rare, commanding huge premiums in the market.

The Perfect [Alternative] Data Scientist

• Domain expertise: capital markets, financial analysis
• Math expertise: statistics, machine learning
• Programming expertise: data engineering, algorithms
• Communication skills and effectiveness
• Business perspective and execution + impact

Source: Abraham Thomas, “Preparing for Success in Alternative Data,” Quandl, presentation at the “Get Ready to Embrace Alternative Data” webinar hosted by CFA Society Toronto on March 17, 2021.

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Baron says, “We look for compromises with recruitment because unicorns are so rare. It’s better to find someone with strength in one area and a lot of potential and grow them along the way.” He also offered some practical tips for people looking to break into the field, which are outlined in the list below.

SO YOU WANT TO BE AN ALTERNATIVE DATA SCIENTIST?
In the midst of chaos, there is also opportunity.

Job Landscape

– Still a relatively fresh field with no formal rules

– You’re competing against established Ph.Ds., so bring something different to the table

Learning

– Start with Python and SQL

– Learn how to ETL (Extract, Transform, Load) data for yourself

– Learn how to ETL and analyze big data in on a public cloud platform (AWS, GCP)

– Go through machine learning / artificial intelligence tutorials on cloud platforms (AWS SageMaker, GCP Colab)

– Go through tutorials focused on analyzing geospatial data and unstructured text

Indirect Job Paths

– Alternative Data startups need people to create quant studies in addition to guiding clients in their own research

– Data Engineering is another potential in-road to gain experience before trying for a Data Science / Quant position

– Marketing Analytics jobs use a lot of the same data for different objectives

Extra Effort

– Supplement lack of experience with Kaggle contests and GitHub repositories

– Meetups focused on machine learning and artificial intelligence will likely have some finance industry attendees

– NETWORK!

Source: Adam Baron, “Primer on Alternative Data,” Refinitiv, presentation at the “Get Ready to Embrace Alternative Data” webinar hosted by CFA Society Toronto on March 17, 2021.

Conclusion
As the investment management industry continues to navigate the ongoing challenges of increasing competition and fee pressure, finance professionals must constantly seek out competitive advantages to beat the market and their peers to stay relevant.

While alternative data alone may not be the silver bullet that firms are looking for, it offers many possibilities for building an investment process and gaining a competitive edge.

While some of the skills the industry requires may be quite different from those of the typical CFA candidate or charterholder, investing the time to gain these skills may be worthwhile considering the industry is still in the early stages and is expected to see long-term growth.