GET EMAIL UPDATES FROM POWERTOFLY
GET EMAIL UPDATES FROM POWERTOFLY
Morgan Stanley Technology

Finding Professional Satisfaction in A.I. and Machine Learning

Nicholas Venuti of Morgan Stanley's Artificial Intelligence Center of Excellence turned his passion for data science into a career as a bank technologist.

In college, Nicholas Venuti spent years researching ways to extract oil from coffee grounds to make biodiesel fuel. After he graduated and began working at an environmental engineering consultancy, he discovered his true passion: data science.

At the heart of his enthusiasm was machine learning, a type of artificial intelligence (AI) that allows computers to "learn" by recognizing patterns and making inferences based on enormous sets of data.

Today, as a machine-learning engineer and data scientist in Morgan Stanley's AI Center of Excellence (CoE), Venuti is figuring out how to harness the raw power of data and turn it into something useful for traders, financial advisors, and investment bankers.

"In investment banking, the problems are enormously complex, and they're changing all the time," says Venuti, who was the first data scientist to join the AI CoE in 2016. "I always find the work both fun and mentally challenging."

The AI CoE, with operations in Montreal, New York, and London, is an internal body that helps enable and scale the adoption of AI and machine learning across Morgan Stanley by providing tools, consulting, and research services to business units and their IT teams.

As part of the group, Venuti works with every corner of Morgan Stanley's operations, from the financial advisors who work with Wealth Management clients to the traders who deal in complex securities.

The complexity and fast-moving pace of data science attracted Venuti to the field. "It's like trying to solve a big puzzle," he says. "You're constantly looking for relationships and tendencies that help explain the problem you're trying to solve."

A Technologist Charts a Career Path to a Bank

A native of western New York, Venuti studied biomolecular chemical engineering as an undergraduate at North Carolina State University, then worked at an environmental engineering firm, where he built systems that analyzed data on oil and natural-gas projects.

"During that time, I developed a knack for solving our company's data problems and building systems to produce insights from these different data sources," he says. "I found myself wanting to perform more robust analyses and, in turn, started taking online courses to add to my skill set." Those classes deepened his interest in data science and prompted his decision to attend graduate school.

At the University of Virginia, where he earned a master's degree in data science, he worked on a team that helped the school's Religious Studies department synthesize the meaning of words in religious texts.

Upon graduation, he was hired by Morgan Stanley to work on AI, a field at the forefront of how companies around the world are using technology. "I was shocked that right out of school I could be part of such a high-profile group within the company," Venuti says.

Wall Street is a natural place for a data scientist, Venuti says, because investment banks have such robust streams of trading data, as well as a flood of external information coming from news, social media, analyst reports, regulatory disclosures and elsewhere.

Financial markets are as dynamic and competitive as the tech industry, Venuti says. "Every day the environment is changing, and as such, the systems we have to build have to be able to adapt to those changes," he said. "We are competing with other firms all trying to do the same thing, so whenever, you solve a problem, you need to move on to the next one to make sure you stay ahead of the game."

Opportunities to Work on Meaningful Projects

One of Venuti's favorite projects was creating a way for traders of complex mortgage securities to determine the risk of those products at the press of a button.

The AI CoE and their partner strategists within the Structured Products Group used natural-language-processing software to comb through the documents related to the securities and flag them for positive and negative comments. The system they built allows traders to quickly review what all the documents are saying about a specific security. The time-saver was an instant hit with traders.

Finding elegant ways to deploy technology is just one goal of Venuti and his colleagues. Another one is demystifying the work they do so that everyone understands just how much it can enhance their roles. "Some people hear the term 'artificial intelligence' and assume that existing systems will be completely replaced or that their expertise will be supplanted," Venuti says. "Rather, the opposite is true: While AI can help inform the decision-making process, we ultimately need the human touch to make the wisest and most sophisticated choices."

This article was originally written by Morgan Stanley. Visit Morgan Stanley's page on PowerToFly to see their open positions and learn more.

What to Write in a Farewell Card to a Leaving Coworker: Quotes and Examples

For the boss you loved, the coworker you hated, and everyone in between

Two things are inevitable when someone leaves your team at work: there will be an abundance of sweet treats (I'm partial to those giant cookie cakes from the mall) and there will be a card passed around for everyone to scrawl the professional version of sweet nothings in. Depending on the "importance" of the person, you may get the bonus activities of farewell gifts and/or an all-team champagne toast.

READ MORE AND DISCUSS
Peloton

A Night of Networking with Peloton’s Women Tech Leaders

If you are a New York based tech professional and you'd like to attend this event, please email your name and LinkedIn URL to events@powertofly.com.

Whether you are a software engineer, fitness enthusiast or both, you won't want to miss PowerToFly's evening of product demos and networking with the women tech leaders and allies at Peloton.

Founded in 2012, Peloton brought top talent together in its Silicon Alley headquarters to create a new concept in fitness. In their words, "We loved cycling but had a hard time finding a workout that consistently fit our schedules, and our at-home workouts never felt quite up to par. So, we set out to create a world-class indoor cycling studio experience on your time, and in the comfort of your own home."

This event is your chance to hear directly from the women tech leaders and allies who make their revolutionary products like the Peloton Bike, Peloton Tread and Peloton App possible. We'll be devoting a large portion of the event to taking your questions and I know the Peloton team wants to hear from you!

The unique evening will take place on Wednesday, February 12th from 6pm to 8:30pm at 125 W 25th Street.

READ MORE AND DISCUSS

Some Men Get a Pay Bump When They Enter Female-Dominated Jobs — How Can Women Benefit Too?

These Researchers Argue It Could Lead to Traditionally Female Jobs Becoming More Valued

Studies have found that as women take over male-dominated fields, the pay drops. So what happens when men start joining female-dominated fields?

READ MORE AND DISCUSS
Diversity & Inclusion

How Inclusion Can Help You Attract and Retain Top Talent

There's a lot more to building an inclusive company than just hiring more people from diverse backgrounds. So, how can you build an inclusive culture that will help you attract and retain a diverse group of employees?

READ MORE AND DISCUSS
Diversity & Inclusion

How This Sales Coach Found Success—And A Career Path—at the Intersection of Tech, Construction, & Sales

A few months ago, Lily Zintak found herself at a crossroads.

She'd been working as a Sales Development Representative in construction management software company Procore Technologies' Austin, Texas office for the better part of 18 months. She'd watched the office grow from less than 200 people to more than 400—and even cut the ribbon when they opened a new floor of offices. She'd made 50-plus sales calls a day, honed an approach to prospecting and connecting with clients that worked for her, and found success. It was at this point in her career, where she had to make a tough decision.

READ MORE AND DISCUSS
Loading...
© Rebelmouse 2019