• Data Science
  • Jesse Moore
  • MAR 27, 2018

Hiring Data Scientists Step 1: Stop Looking for Data Scientists.

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Dear world,

We are looking for someone to fill an upcoming gap in our business model. We are not exactly sure what you will be doing, but we are sure that our shareholders will love the idea that we have Data Scientists. You will report to someone that does not understand what you do, and you will often be met with skepticism when you present your solutions to management. Candidates must possess the following:

  • B.Sc in Computer Science
  • M.Sc/PhD in a quantitative field
  • 3–5 years in a research focused position, and experience with backend frameworks, application development, web hosting and a deep knowledge of both neural networks and statistical methods
  • 5 years programming experience
  • 2–3 years in database management
  • 5 years of experience in our domain (Healthcare, Marketing, etc)
  • Advanced knowledge of SQL, Python, R, Matlab, Java, C, C++
  • 2–3 Published research papers in Artificial Intelligence, Natural Language Processing, or Computer Vision (all three preferred)
  • Experience with Spark, Hadoop, and Pig... and Horse

This Person Hardly Exists

How many people in the world do you think fit this bill? And what number of those people have the soft skills to be customer facing, client facing, management facing, yet analytical, creative, and intelligent. We are asking the wrong things from Data Scientists and we are looking in the wrong places. It is strange that a Job Ad for Apple often has less than half the requirements for XYZ Consulting Inc.

There is no possible way that a Data Scientist will use all these tools at one company, and even less likely that someone knows all these languages. Data Science is more about the intelligent use of programming, rather than programming itself.

You Are Not Hiring Programmers.

Stop focusing on degrees and credentials, but on proven real world experience. It does not even necessarily have to be as a formal Data Scientist. Here is my main goal when I look to bring on a new member to our ML team:

What We Want:

  • Intelligent, explorative, and passionate people over experienced.
  • People with an ability to take cloudy, uncertain ideas, and build them into finished products

What We Offer:

  • Provide an interesting team and strategy and give them the opportunity to work on cutting edge technology
  • Give them room to grow, understand what they want to learn and help them get there
  • An understanding that everyone in the team is equal

Start With a What Matters

The most difficult skills to find when it comes to Data Science are not tied to a degree or specific work experience. It is the explorative nature, the push for optimisation, the results mindset, the never give-up attitude, and the willingness to learn that makes a good Data Scientist. If you give me someone with those soft-skills, some basic programming ability, and an understanding of mathematics I promise you they will become a great Data Scientist in a relatively short period. When I look to hire people in my team, these are the most important skills. Everything else is gravy.

To be sure, degrees and experience can be a good judge of ability. But those come at a high cost —It dramatically shrinks the size of the pool you look to draw from, and it creates a confirmation bias whereby we continue to push for more and more credentials.

Here is a small snippet from a position description I wrote:

Expectations
We are building a team that prides itself on high standards and executional excellence. You will be judged on your results more than your code. Responsibilities, challenges, and opportunities will grow rapidly based on objective meritocratic criteria.
Major Responsibilities
- Assist with the design, development and evaluation of both Deep Neural Networks and traditional Machine Learning models.
- Assist in the creation of scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Commitment to being a willing partner in an execution oriented team.
- Results Focused — Capable of delivering good work on tight deadlines

Create a Job That You Would Want To Take

When I am hiring, I spend hours with the position description over several days. I write it, I re-rewrite, and I write it again. I build a role that fits the needs of our team, has room to grow, provides great learning opportunities, and offers something exciting. Without that, people will become bored and bitter over time. It is easy to identify a business need for a specific role, but it is often difficult to define exactly why you need a Data Scientist and what they will be doing. It is your job to think this through before starting your search.

To be sure, there will always be parts of a job that people do not like, but it is a tragedy to go to work everyday doing something you hate. When I go to work excited, motivated, and driven I produce 5x the work I would otherwise. As a team leader it is a necessity that I provide that environment for my team. It is best for the individual, the team, and the business.

Managers Should Write Their Own Position Descriptions

If you can not spend the 3–5 hours it takes to write a proper job description, then you do not need the position enough.

The number of times I have read position descriptions that sounds generically written by Human Resources is shocking. It sometimes feels as if the same position description is repeatedly recycled by 100 recruiters. You are often left with no idea what you are doing, what the team is like, or whether you have the 35 skills required to fill the job.

Be More Interested in How People Think

Since I am not a computer scientist or Ph.D, I may be a bit biased (I am a Mechanical Engineer). I was taught how to take complex problems and break them down into smaller tasks, just as programmers are. However, I truly believe that it was not until my undergraduate engineering degree that anyone expected me to think. This skill is so under-utilised and under-valued it is shocking to me.

Looking for, and finding people that can think critically, creatively, and intelligently is hard. That is why finding Data Scientists is so hard —Understanding how to take data, explore it, understand it, and model/present it in a way that is valuable is hard. Taking billions of unstructured data points and extracting information, transforming it, augmenting it and generating actionable data/predictions is difficult and does not have pre-defined rules or applicable systems.

Perhaps the most valuable skill a Data Scientist needs is the ability to handle open problems without a defined solution. He/she needs to be able to provide value when the value is not defined — they often need to understand this and get there on their own. He/she needs to be able to choose from the hundreds of potential outcomes to find the one that best fits the problem and business at hand.

A true Data Scientist:

  1. Understands the concept of value creation
  2. Understands business
  3. Understands how different techniques and models can be used to create value your data
  4. Handles complex, open problems methodically, and with interest.
  5. Doesn’t need to be a good programmer.

Will this make your job hunt easier? Probably not. But, at least you will looking for real-live people, AND you will be looking for the right set of skills. When you force yourself to look for this type of person, you force yourself to think about why you need a Data Scientist in the first place.

It will be better for you, it will be better for your team, and it will be better for your company.

Boston city bkg

Made in Boston @

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