Pandata: Developing the Cleveland Data Science Talent Pool

Pandata is a young and fast growing data science consulting firm out of Ohio founded by Cal Al-Dhubaib, the first data science graduate from Case Western Reserve University.  As PanData began expanding its data science team in its early years of operation, it needed a solution that would help the small founding team confidently and more quickly scale the process of hiring data scientists. With senior managers focused on winning and managing projects, the firm needed an efficient way to assess data science skills. Here’s Pandata’s story about using the QuantHub platform to achieve that.

A Small Company Scaling Steadily in the Data Science Space

Hannah Arnson is the lead Data Scientist at Pandata.

Pandata started out primarily focused on marketing analytics projects.  As the company’s lead Data Scientist Hannah Arnson puts it,

“Everywhere there’s data. Marketing just happens to have a lot of data.”

Marketing analytics projects are still a significant part of Pandata’s portfolio.  However, by leveraging this “front door” to clients in need of marketing analytics support, Pandata has been able to demonstrate the value of data science in many other areas.  The firm has now expanded into a wide variety of industries and project areas such as cybersecurity, higher education, arts and entertainment, and healthcare operations.
Pandata typically works with local and regional mid-sized businesses.  Recently it has begun working with larger enterprises and on out of state projects. The company expects this trend to continue and will ramp up hiring to meet growing client needs.

The Need for Data Science Skills Assessments

Hannah Arnson is quick to point out that Pandata’s growth is fueled by a real market need.

“There’s a real need in Cleveland and other Midwest states. There are companies that need data science.”

She points out however, that in Cleveland the pool of talent with data science skills is limited.
Enter Pandata to fill the skills gap. But with a small team, no formal human resources function, and many opportunities for data science projects on the horizon, Pandata needed a solution to vetting data science skills that was effective and which did not take too much of the lead data scientists’ time away from projects.
In addition, being a new company management found that coming up with the various types of technical skills questions and problems that would effectively vet data science candidates was an additional time consuming challenge.
Hannah emphasizes that the team had so much else going on they needed a quick solution,

“We were looking for a way to technically vet candidates that didn’t require a huge effort like coming up with statistics and other multiple-choice questions on our part.  When we found QuantHub, it addressed a really useful part of the hiring process to have that automated vetting where we don’t have to do that much.”

How Pandata Uses QuantHub

Pandata started out using QuantHub to vet and hire for Data Scientist roles.  Over time, as the company has expanded, it has begun using QuantHub to assess the skills of entry level Data Analyst candidates with up to 3 years’ experience. This has enabled the company to expand its recruitment pool. The company is now moving towards a strategy of hiring and training Data Analysts internally to become Data Scientists. Hannah explains the reasoning,
“We found that this is a really effective way of getting talent that we work well with, that fits our mold and which sticks around. Given the talent pool in Cleveland, it opens up the possibilities.”
Pandata has found too that it is challenging to vet and hire Data Scientists only to find out that they don’t necessarily have the technical skills you would expect. It is also difficult to keep them around.  Retention is a big issue for Pandata as its client projects and relationships tend to have longer term horizons.
That said, the firms recognizes that a certain amount of turnover is good, as Hanna explains,

“We’re devoted to developing the Cleveland data science pool so that the data talent will spread.”

Advantages of Using QuantHub in the Hiring Process

With projects picking up and customer relationships expanding, Pandata’s goal is to double staff over the coming year. That’s a great situation to be in, but it makes hiring an even more pressing issue.
For one of the more recent Data Analyst positions that Pandata was trying to fill they received around 100 applicants! With the lead Data Scientists busy on projects, they used QuantHub to assess several top candidates.
What kind of skills are is Pandata specifically looking for? Programming languages are important as well as statistics, as Hannah explains,

“They need a minimum of being able to do R and Python…We use QuantHub assessments to make sure candidates have a basic set of skills and then we give them a data science challenge at the same time.”

Another key benefit that QuantHub delivers is time saved. Explaining how much time it takes to recruit, evaluate and make a data science hire, Hannah says,

“It takes too much time! There are 3 of us (CEO, COO and herself) involved in the hiring process and it is spread out over a few days. It’s a good ½ day of interview work for each of us, plus the time to read resumes and applications, do initial telephone screens and assess for a cultural fit, which is a really big factor for a small company like us.”

Lastly Hannah explains that QuantHub assessments give the team an objective and fair comparison of each candidate.

“It’s helpful to have a concrete and objective metric across all the candidates.”

For example, recently Pandata assessed a candidate that scored in the middle of the pack on the QuantHub test, but did an impressive job in their interview presentation, explaining complex concepts in a way that a businessperson could understand. With QuantHub they have information to objectively assess the tradeoff between scores and other key skills.