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How Signifyd risk analyst Dan Phan charted his path to data science

Read the State of Fraud Report 2021

Read the State of Fraud Report 2021

The cover of the state of fraud 2021 report

Dan Phan joined Signifyd because he wanted to experience a startup’s fast-paced atmosphere and wealth of career opportunities. 

“I felt that my career growth would be more valued at a smaller company,” says Phan, now a quantitative risk analyst at Signifyd. At the large Silicon Valley tech company where he had been a contractor, it seemed like contractors were always “fighting tooth and nail to become full-time employees.” 

Many contractors at Signifyd also want to move to full-time roles, of course, but at Signifyd, he feels that his contributions are more visible. And his managers have encouraged him to build his skills – and even helped him move to a new department.

Portrait of Signifyd quantitative risk analyst Dan Phan

Dan Phan, quantitative risk analyst

Phan started at Signifyd as a manual review agent in October 2017, first as a contractor and then, after about six months, as a full-time employee. Within about a year, he was promoted to a senior analyst role. All the while, he learned about trends in online fraud and the unique ways fraudsters attempt to sneak transactions through Signifyd’s risk system.

“I quickly became interested in analytics,” he says. “I started asking questions whenever I received new project assignments: What else can I do to help the data science team?”

A new role in data science

A manager noted his interest and started teaching him how to code. Phan kept practicing and asking to learn more. That manager ultimately suggested him for an opening on the data science team, based on his interest, newly acquired skills, and knowledge of the company and its products.

One Friday afternoon in March 2020, Phan received a call from a manager asking him if he would take a position with the data science team. And could he start Monday?  

“It was a ‘yes’ in a heartbeat because the new skills I would be learning are great for my career growth and new opportunities in the future,” Phan says. 

After a three-month trial period, his move to the data science team as a quantitative risk analyst was made official.

In his new role, Phan monitors online traffic, looking for pockets of fraud that indicate that fraud rings have discovered new vulnerabilities. If the teams find a pattern of approved purchases that turn out to be fraudulent, “we have to figure out the commonalities and stop the model from approving those orders,” Phan says. They then write code to provide protection. Meantime, Signifyd’s financial guarantee protects merchants from any losses.

Eliminating loopholes to protect merchants from fraud

“Fraudsters are trying to find loopholes,” Phan says. “We are the ones who find those loopholes and patch them up. There’s kind of a black market where fraudsters communicate – one person figures out a loophole and will announce it on social media. The point is to stop it before it gets too big.” 

Cross-departmental moves, like the one Phan made, are encouraged at Signifyd.

“We encourage employees to explore new career paths that interest them, first by talking with a manager in the department that intrigues them. The conversation starts with a discussion about what that team’s career path looks like and what skills are needed to develop into the various roles involved,” said Cassandra Mingus, Signifyd’s director of talent acquisition. 

For Phan, the new job has opened up a world of new career options.

“When I moved over to the data science team, my new managers gave me weekly lessons on how to code and do things in this new role,” Phan says. He didn’t have a coding background previously, and now he can code on multiple platforms. “I learned everything on the job, which you won’t get anywhere else.”

A bright future working with data to improve performance

The data science team has people in two types of roles: analysts and data scientists. “As an analyst, I mainly write code to patch holes and analyze data to figure out certain trends,” Phan says. 

The data scientists work on creating new models. “Not only do they know how to code, they know how to build their models,” Phan says. “I’m hoping to slowly work my way up into that type of role.”

His managers allow him to take time during the day to learn new skills – online classes or tutorials. 

“I definitely wouldn’t be in this position without the guidance of the managers of this company,” Phan says. “Managers push you to do more, but they also give you the resources to do it.”

Phan has been able to achieve the goal he had when he joined Signifyd: to be able to build his skills and have a good career path. “They ensured that,” he says. “As long as you work hard and keep asking for more, they’ll have more to give.”

Feature photo by Getty Images; Dan Phan portrait by Signifyd


Margaret Steen

Margaret Steen

Margaret is a writer, editor, writing coach and regular contributor to the Signifyd blog.