Improving the Number 1 Skill for Data Professionals

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⸻ Beyond Data

Strong communication is the foundation for all success in data - practice it

This will start a series of posts on a topic dear to my heart – honing your communication skills to amplify your impact.

More than anything else, how you communicate will be the dominant factor in your success as a data professional (especially in management and leadership roles). Hear why and what you can do to turn communication into a strength.

The wrong question

I get asked a lot by aspiring data professionals about how to and what they should be focusing on to improve.

Things like:

  • What framework should I learn next?
  • What models should I be using?
  • Should I learn Julia or Spark?

While these are all good things to consider (in the proper context) for most people, they’re not where you should be focusing. Being that rare data scientist who knows Julia over their peers is only going to assist in some niche roles or industries — it’s one of those skills that might be used to differentiate between two strong candidates.

Wouldn’t it be better if you built the foundations to be a robust and standout candidate across all roles and industries?

Once you’re beyond a certain threshold of technical understanding, it is tough to keep advancing and make meaningful improvements to your technical ability. This usually comes with niching down and mastering some specifics in the field.

There are, however, general skills that are always useful and sorely scarce across all data roles. Things like:

  • Project management
  • Research methods
  • Teamworking (yes this is a skill you and you can get better at it!)
  • Timekeeping (this too!!)

In my opinion, however, one skill beats them all. You guessed it, communication.

This is a no-brainer, right? Communicating effectively is vital for any profession and for life, but I want to highlight its importance in business.

I’ve worked with several super-talented people that struggled to have the impact you’d expect because they were held back by their communication. Worse, many talented people think they’re above this, and the work should speak for itself — it won’t.


It’s your job to translate your ideas into the clearest, easiest-to-digest form possible without compromising on the content of the message. In many situations, you’ll be the expert in what you’re discussing — you’ll have been hired for your technical expertise and are required to translate that to non-technical stakeholders, or you’ll be in a technical team. You’re relaying the outcomes of your project to the broader group. Either way, it’s about context.

It reminds me a lot of the famous experiment by Elizabeth Newton at Stanford — study participants were made to tap out a tune to others and guess the likelihood it would be guessed correctly; those tapping the tune massively overestimated the ease with which it would be guessed. This is dubbed “The Curse of Knowledge” and is well-studied.

Curse of knowledge

Essentially, it’s hard for anyone to discount what they already know when explaining something to someone else. Data professionals are especially bad for this. We often assume a level of understanding (or even interest!) that isn’t there and communicate at completely the wrong level.

Although I have a technical background, I tell my teams to write their presentations, demos, and documentation as though they’re communicating with an idiot. You’ll hear me band around the term “idiot-proof” a lot.

Assume I know nothing, and you need to communicate so that I get your main points. The algorithm or mathematics might be interesting to you, but for many non-technical stakeholders, it isn’t. Worse, high-level leaders within many businesses may consider this intellectual snobbery or time-wasting.

How do you improve at this? Practice.

Run lunch and learn sessions for non-techies or people with little experience in your field. Ask your family or friends that don’t work in tech if you can quiz them on it. Getting this right will work wonders and save time getting bogged down in technical detail when it isn’t needed.

Written communication

This skill should come with time as you document your work and collaborate with a team. Try to keep concise and avoid the use of complicated words or language.

I’ve kept a written journal of my working day for my entire career. I learned early on in my doctorate that I needed to write things as explicitly as possible and keep track of references like my life depended on it. If you’re ever on a call with me, you’ll be fully aware of just how much I write down.

We work in a broad field with many deep technical areas; it’s easy to forget something you knew six months ago. Getting into the habit of good note-taking should improve your writing.

Don’t be afraid of the review and editing process; a harsh editor is a blessing. I went through a lot of this pain writing my thesis, and my writing is much better for it. Having someone else objectively review your writing is gold. If you’re finding it hard to read what you write, start a blog; plenty of people online are eager to help. If you start a blog after reading this and want it reviewed, reach out, and I’ll tell you what I think.

Finally, I’d recommend using a tool like Grammarly – it’ll stop you from second-guessing your grammar and help with consistency.

Verbal communication

Most data professionals I’ve known have struggled more with verbal communication than written. There are a load of tricks and tips for getting better at speaking. The top three I tell people when coaching this stuff are:

  • Slow down (a lot) — one thing many techies tend to do is talk too fast, especially when they’re excited. Try to avoid this. Try to actively slow down, and think of the kind of pace a politician or actor uses when giving a rehearsed speech or monologue.
  • Pause more, for longer — this seems counterintuitive, but add longer pauses to your speech. Leaving gaps can be powerful and punctuate what you’re saying. It exudes confidence. It also gives others a clear signal that they can cut in with questions or another point if they need to, and won’t have to talk over you or wait too long. It also gives you an excellent opportunity to review the body language cues you’re getting from the room and tweak your message accordingly.
  • Get to the point — too often, I’ll hear excellent points get ruined or missed because the speaker goes off on a tangent or down a rabbit hole. You’ve probably witnessed someone get lost and forget what they’re saying. In a work context, this can be a damaging reputation to have and can lead to people switching off every time you start speaking. Try to be concise and keep on track, and expand on your points only if asked to or absolutely necessary.

Visual presentation

This probably hurts my soul more than anything else mentioned in this list. Please take some time to learn to use visuals effectively. Please.

Too often, I see folks present brilliant work with results plotted on the wrong chart type, with bad axes, and unclear, ugly, squinty visuals. Whether you’re writing for journals, giving presentations, blogging, or just documenting your results in your Jupyter notebook — your charts are what most people will gravitate towards. Make them hit home.

I’m a big believer that if I can’t immediately (within a few seconds) understand what’s going on in a chart, it’s probably a bad visual. If someone has to walk me through or explain a chart, there’s a good chance it could have been simplified or presented better.

There are a lot of resources out there to draw from. Sometimes a mixed bag, but r/dataisbeautiful is an excellent place to see what others are doing (just be wary, beautiful charts aren’t necessarily good).

I recommend you familiarise yourself with the Financial Times Visual Vocabulary — this is an excellent standard to strive for. There are some implementations for things like Tableau and Power BI out there too.

Sometimes complex figures are necessary, in which case, try your hardest to apply some of the points from the fantastic Visual Display of Quantitative Information by Edward Tufte.

Final thoughts

With anything, targeted practice will lead to significant improvement across the board. Some of these things might come naturally to you, while others won’t. Don’t be afraid to reach out to mentors, colleagues, or even the wider community — there’s nothing like starting a blog or attending a local meetup to hone your skills. You might enjoy it.

Hopefully, you found this helpful. Please let me know if there are any tips you think I may have missed — I’m still learning too!

All the best,


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