BlackRock Ramps Up Data Science Team As It Builds Dynamic Pricing And Auto-Bidding Engine For Security Lending

By Dan Anderson ● May 7, 2019

Global investment management company BlackRock is ramping up its data science team in order to build a dynamic pricing and auto-bidding engine for its security lending business. In its first year, BlackRock’s Data Science team has grown to more than 30 data scientists and data engineers. BlackRock’s AI Labs was formed last year in order to accelerate innovation and technology in artificial intelligence and to have a firm-wide impact using data science for solving strategic problems.

Based in Palo Alto, California, this team is headed up by BlackRock managing directors and co-heads of the company’s AI Labs Dr. Sherry Marcus and Dr. Rachel Schutt. And it is directed by Stanford professor Stephen Boyd, according to Business Insider. And BlackRock’s AI Labs staff is also actively recruiting more. For example, BlackRock has an opening for a senior data scientist position.

“We are looking for candidates with unique backgrounds and diverse skill sets with fresh perspectives to accelerate and amplify our efforts to make an impact at BlackRock. Data Science Core aims to bring best of class technologies, analytics, and insights to the entirety of the firm and to our clients utilizing data from a wide variety of sources including text, news feeds, financial reports, time series transactions, logs, imagery, and real-time data,” says the job description.

By automating repeatable tasks like generating insights based on the variety of sources mentioned on the job description, it frees up staff members so that they can work on tasks that require human intelligence.

“Ninety percent of the world’s data was created in the last few years (source: IBM). This explosion of data is broadening the way asset managers view the world. But this data did not just fall from the sky in a perfect package. It is unstructured, unwieldly and extremely time consuming to digest. Machine learning and artificial intelligence techniques allow us to comb through this often messy data to glean insights never before thought possible—like the speed of construction in China, foot traffic into major department stores and sentiment picked up from thousands of online employee reviews. When combined with millions of other data points, these factors help asset managers make smarter investment decisions that impact our clients’ financial well-being,” wrote BlackRock managing director / Head of Aladdin Product Group Joseph Kochansky in a blog post last year.

Currently, BlackRock manages more than $6.2 trillion in assets on behalf of its investors worldwide. Given how massive BlackRock’s asset platform ranges, it has become an important space for data scientists and engineers across all areas including investments, sales, marketing, operations, product, UX, etc. to make a large scale impact.