J.D.Long is the current AVP Risk Management at RenaissanceRe and has a 15 year history of working as an analytics professional.

Follow Peadar’s series of interviews with data scientists here.

What project have you worked on do you wish you could go back to, and do better?

I’ve been asked this question before.

Longer answer: Interestingly, what I find myself thinking about when asked this question is not analytics projects where I wish I could redo the analysis, but rather instances where I felt I did good analysis but did a bad job explaining the implications to those who needed the info. Which brings me to #2…

What advice do you have to younger analytics professionals?

Learn technical skills and enjoy learning new things, naturally. But, 1) always plot your data to visualize relationships and 2) remember at the end of the analysis you have to tell a story. Humans are hard wired to remember stories and not numbers. Throw away your slide deck pages with a table of p values and instead put a picture of someone’s face and tell their story. Or possible show a graph that illustrates the story. But don’t forget to tell the story.

What do you wish you knew earlier about being a data artisan?

Inside of a firm, cost savings of $1mm seems like it should be the same as generating income of $1mm. It’s not. As an analyst you can kick and whine and gripe about that reality, or you can live with it. One rational reason for the inequality is that income is often more reproducible than cost savings. However, the real reason is psychological. Once a cost savings happens it’s the new expectation. So there’s no ‘credit’ for future years. Income is a little different in that people who can produce $1mm in income every year are valued every year. That’s one of the reasons I listed “be a profit center” in the post John referenced. There are many more reasons, but that alone is a good one.

'Be a profit center'. #datascience Click To Tweet

How do you respond when you hear the phrase ‘big data’?

I immediately think, “buzz word alert”. The phrase is almost meaningless. I try to listen to what comes next to see if I’m interested.

What is the most exciting thing about your field?

Everybody loves a good “ah-ha!” moment. Analytics is full of those. I think most of us get a little endorphin drop when we learn or discover something. I’ve always been very open about what I like about my job. I like being surrounded by interesting people, working on interesting problems, and being well compensated. What’s not to love!

(image credit: T Young, CC2.0)

Previous post

Improving the Accuracy of Big Data Analysis

Next post

"Invent the future." - An Interview With Mike Gualtieri, Forrester's Principal Analyst