Sometimes we forget the humans behind the tech in our ever busy world. DSF is fortunate enough to know some incredible tech leaders across the world and has the privilege of hearing them present at our events. That being said, our Speaker Spotlight sets the stage to get to know our speakers on a more personal level and connect them with our growing community. Read the mini interview below!

A bit about Ned:

Ned has over 8 years’ experience as a data professional in finance, events, publishing, and politics. He works in SQL, Power BI/DAX and Python, with additional competencies in D3 and front-end website development. He believes that in the era of AI, human-driven judgement, innovation, decision-making and creativity will become more important, not less.

How did you start out in your tech career?

Literally grasping what a VLOOKUP in Excel was unleashed in me the core developer/data analyst tendency of trying to outdo myself technically task-by-task, regardless of whether the task required the technical complexity!

What are the signs of success in your field?

The more you’re up at 2 am blinking at a computer screen having solved a difficult problem with data or coding, the more battle scars and high-quality hard-to-achieve wins you are accumulating.

What is the best and worst thing about your job role?

Data scientists, engineers and analysts have the privilege of doing work that is varied, intellectually stimulating, and well-paid. But in many organisations they are in a no-mans-land of neither being business stakeholders nor fully fledged IT/dev, which means their requirements and perspectives are often misunderstood and poorly advocated for.

What can you advise someone just starting out to be successful?

Shameless plug – UCOVI (www.ucovi-data.com/about). This stands for Understand-Collect-Organise-Visualise-Interpret, which are all the disciplines that someone at the beginning needs an awareness of to understand what the essence of data work is.
Understand is the process of assessing what the data processes, assets, and culture are like in any organisation and what can be accomplished with them. Collect is the process of gathering data (APIs, public datasets, effective survey design). Organise is cleaning, blending and joining datasets (ETL) and is the code-y bit, along with Visualise, which is charts, graphs and BI tools. Finally, Interpret is the skill and process of assessing and communicating the insights produced by all of the above.
Entrants into the datasphere are bombarded with competing tools and tech to learn – the supply market for tools and how quickly it moves is intimidating even to those with experience. The UCOVI framework is a good way to think about how all the tools, technologies and common tasks can be grouped up into buckets of core aptitudes to build.


How do you switch off?

Not very easily! I’ve had to get better at turning up to social events on time even though my code wasn’t working over the years. What has really helped has been the practice of finishing each work day or hobby coding-session with a diary entry in my notes where I write up everything I’ve done that day, where I’ve got to, and probably causes of the mystery code failure and lines of investigation for next time. Doing this provides a good “To be continued next episode…” bookend to my work which allows me to  be excited to resume (whenever it happens) but also happy to walk away from my half-done work.

What advice would you give your younger self?

I’d go full Gary Neville on this one and say “Pints cost you leagues!” Being hungover on Saturday or Sunday is a waste of the best time you have to really push ahead, or at least do the things you love and do them well.

What is next for you?

I’m looking to add desktop app and GUI building to my repertoire and have just started learning C#.

If you could do another job now, what would you do? Why?

I would go back to university and do a Computer Science degree. I’ve transitioned into data analytics and tech from a humanities and social science background and still feel like I’m playing catchup with those who truly know how to talk to computers.

What are your top 5 predictions in tech for the next 10 years?

I’m going to short change you here and only give two, but they both relate to things that will be in wide circulation in 2033, and begin with V…
1. Virtual reality glasses.
2. VBA. Microsoft’s legacy coding language of spreadsheet automation will still be limping on and propping up corporate tech stacks like Jenga.

Watch Ned’s session at the Data Science Festival here

Thank you to all our wonderful speakers for taking part in our Speaker Spotlight!

Want to become a DSF Speaker? Apply here!