I co-founded a company! Meet Problem Forward Data Science · Simply Statistics


I’ve some thrilling information about one thing I’ve been engaged on for the final 12 months or so. I began an organization! It’s referred to as Problem Forward knowledge science. I’m pumped about this new startup for lots of causes.

  • My co-founder is one in all my households closest pals, Jamie McGovern, who has greater than 2 a long time of expertise within the consulting world and who I’ve identified for 15 years.
  • We’re making a cool new mannequin of “knowledge scientist as a service” (extra on that beneath)
  • We have now a problem forward, not solution backward strategy to knowledge science that grew out of the Hopkins philosophy of information science.
  • We’re headquartered in East Baltimore and are creating superior new tech jobs in a spot the place they haven’t been traditionally.

Drawback Ahead, Not Resolution Backward

We have now all the time had a “drawback ahead, not answer backward” strategy to statistics, machine studying and knowledge right here at Merely Stats. This has grown out of the Johns Hopkins Biostatistics philosophy of beginning with the general public well being or medical drawback you care about and dealing again to the statistical fashions, software program, and instruments you have to resolve it.

This concept is so necessary to us, it’s within the identify of the corporate. Once we work with individuals our first objective is to seek out out the issues and questions that they genuinely care about, then work backward to determine methods to resolve them. We don’t are available with a specific predetermined algorithm or technique. One of many first questions we ask individuals isn’t about knowledge in any respect, it’s:

What query do you want you might reply about your enterprise (ignoring when you have the info or to not reply it but)?

My favourite instance of that is Moneyball. This is among the basic tales about how the Oakland A’s used knowledge to achieve a singular benefit. However one of many key messages about this story that usually will get missed is that the info weren’t distinctive to the A’s! Everybody had the identical knowledge, the A’s simply began with a drawback that they wanted to unravel. They wanted to discover a distinctive solution to win video games that wasn’t as costly. Then they moved ahead to trying on the knowledge and realized that on base share was cheaper than residence runs. So the A’s used a “drawback ahead, not answer backward” strategy to knowledge evaluation.

Utilizing this strategy we have now labored with firms with all kinds of wants. Our primary capabilities are in knowledge technique, knowledge cleansing and analysis high quality database technology, modeling and machine studying, and knowledge views by means of dashboards, reviews, and shows.

Knowledge Scientist as a Service

There are an enormous variety of knowledge science platform firms on the market. A few of them are producing superior instruments, however as any severe knowledge analyst will let you know we’re years from automating actual knowledge science. We’re solely very just lately seeing formal definitions of what success of a data analysis even means! So it isn’t shocking when normal objective platforms like IBM Watson struggle with specific problems – the problem isn’t specified clearly enough for a platform to solve it yet..

The explanation there are such a lot of platforms is that its straightforward to promote the “cool” a part of the issue – say constructing an AI to categorise photographs or drive a automobile. However typically the deeper drawback is (a) determining what you even need to or can say with a set of information set, (b) amassing a set of disorganized knowledge, © getting purchase in from teams with totally different motivations and knowledge units, (d) organizing ugly knowledge from totally different sources or discovering new knowledge you may want, and (e) placing your solutions in context. These issues are extra like “glue” that comes between every of the platforms. We have now a phrase we like to make use of:

To unravel your knowledge drawback you want an individual, not a platform

So we have now arrange a “platform” that allows you to scale up and down the quantity staff members you need to resolve knowledge issues, similar to you’d scale up and down the variety of servers or instruments that you just use on AWS.

This implies if you’re an early stage startup we may help you scale knowledge science earlier than you may afford to rent a complete staff. Even if you’re a non-profit or a small educational group we will scale up or down to fit your wants. And if you’re a giant firm we will present utility knowledge science for initiatives with tight deadlines.

Working with pals and constructing East Baltimore

The factor that will get me most enthusiastic about this new journey is working with my actually shut pal Jamie. It’s been enormous for me to be taught in regards to the ins and outs of beginning and working a enterprise with somebody who has a long time of expertise within the consulting trade.

It’s additionally thrilling to have the ability to headquarter the corporate proper in East Baltimore and to work to upskill and develop expertise right here in a neighborhood I care about.

Like what you hear? Get in contact

If you’re on the lookout for knowledge science work we’d love to listen to from you! Whether or not you might be an educational, a non-profit, a small startup, or a giant enterprise our utility mannequin means we will work with you.

If you’re excited by working with us contact us right here:


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