Position descriptions and selection criteria are detailed documents which give very specific details of what the employer is looking for in a future employee. They give very specific skills sets and ask you to give selection criteria responses showing how you meet those skill sets. In your response you give case studies of things you have done that show you have those skills. The skills could include communication, teamwork or leadership, project management, financial planning; the list is endless.
For all the details in the position description though, how do you step back and work out the type of person they are looking to employ? How do you see what the forest looks like for all the trees they are describing?
I was helping a customer preparing for a data scientist job interview recently. He had the skills to do the job, had written a comprehensive selection criteria response and was a good candidate for the position. Unfortunately, he was focussed on preparing to be able to show how he met all the skill requirements but couldn’t get a vision on “the person” they were looking for.
Having “all the skills” for a role is one thing, but, being the person who will be a good fit for the team and the business is another. In my Selection Criteria Course I talk about mission and values, and how being a person that aligns to those is important. It is important because a math savant may have all the math skills for an analyst role, but if the role requires communication with teams and people to determine business needs, a savant is possibly not the person you want in that role.
I’m using the extreme example of a savant in recognition that people come in all shapes, sizes and individual differences, and any individual tendency to behaviours that might place a person on the autism spectrum should never exclude someone from employment. I am an INTJ on Meyers Briggs and arguably to anyone who knows me would be a good example of the correlation between Asperger’s and INTJ personality type and/or high functioning autism correlating to the INFJ personality type.
But I digress. Having “all the skills” for a role is one thing, but you also need to be the person they want in the role.
The accountabilities for the role I was assisting the customer with are shown below.
Have a read and see if you can pick up the key themes from the detailed list. I’ll continue to discuss this after the list:
- Support performance driven and customer experience culture by designing and developing data analysis products which are best practice, accurate, relevant and represent a complete picture.
- Research, test and apply statistical modelling and analytical techniques using tools and software to support stakeholder requirements, outlining the sensitivities and limitation of applying data to decision making.
- Analyse, quantify and communicate passenger transport trends and opportunities to stakeholders through formal correspondence and briefings to support network performance and customer experience improvements.
- Assist in the investigation, design and implementation (including re-engineering) of cloud data warehousing and business intelligence solutions.
- Contribute to the documentation of the data analysis platform – data management plan and training materials, including the associated data analysis products.
- Proactively invest in the development and management of internal and external stakeholder relationships and participate in conversations to help translate their needs into requirements and measurable outputs.
- As required, mentor peers and stakeholders on the use of data analysis tools and interpretation of data findings, contributing to maturity as an insight and evidence-based organisation.
- Actively participate in performance conversations to build and support a culture of performance improvement.
How did you go?
Who is this Person?
It’s a data science role so take it as a given, they want a data scientist.
I’ve coloured some keywords from the list that is you look at just those words you should see a theme.
- best practice, accurate, relevant and represent a complete picture
- support stakeholder requirements
- communicate trends and opportunities to stakeholders
- support network performance and customer experience improvements
- cloud data warehousing and business intelligence solutions
- documentation of the data analysis platform
- development and management of internal and external stakeholder relationships
- conversations to translate their [stakeholder] needs into requirements/outputs
- mentor peers and stakeholders
- contributing to maturity as an insight and evidence-based organisation.
- support a culture of performance improvement
A lot of that I know from experience. You may be reading and thinking that’s great for me to do but how do you do it yourself?
I know I still haven’t answered the question of who they are looking for, I’m getting to it.
Try A Word Cloud
Using a free online word cloud generator, this is what the accountabilities “look like”:
As I said, it’s a data scientist role so take that as a given. As it’s given, you can remove those words. Taking out all the data scientist words (data, performance, analysis) it gives this:
Look at the words that stand out in the word cloud and the list I coloured – support, conversations, stakeholders, culture, customer experience.
What do they all say when put together?
They want a data scientist who is a people person!!
They want someone who can engage the business, engage stakeholders and understand all of their needs. Also they want someone who can advise the business. Finally, they don’t just want facts and numbers, they want advice. This comes through in saying “complete picture” and “customer experience improvements” – they are business objectives and customer outcomes. The goal of the analyst is to achieve on the ground, customer experience changes.
They want a data scientist who can communicate with the business and customers. One who can identify outcomes that matter. Someone who has the data analytic skills to do a thorough, best practice defensible analysis that they can communicate to the business.
You want to be as most like the person they are looking for in order to resonate with the panel.
It allows you yo make sure as you are giving selection criteria responses that align with the qualities they are looking for. You don’t have to go out of your way to do that either. Simply working in phrases like best practice when describing how you do your work, mention that you ensure you document processes and when giving examples of analyses you have done, make sure you mention they were focussed on customer outcomes and/or improvements.
Those few simple words alone will show you are the kind of person they want. If the discussion after all the interviews comes down to two equal applicants, having those tipping points could weight the discussion in your favour.
Finally, you are selling your whole self, not just your skills. You are selling your attitudes, way you do your work, how you consider customers in what you do; all of those things should be as close as possible to the person they are looking for!
If you can make a final statement you could use the opportunity to position yourself.
What does position mean? Taken from marketing (because a job interview is about selling yourself) it is:
Market Positioning refers to the ability to influence consumer perception regarding a brand or product relative to competitors. The objective of market positioning is to establish the image or identity of a brand or product so that consumers perceive it in a certain way
Take the opportunity to make a short statement you have prepared ahead of time that shows them:
- You are the person they are looking for, and,
- You understand what they are looking for because you prepared.
That could go something like:
I consider I am the best person for this job because I bring the data scientist skills you are looking for as I’ve described in all the analytics and business advice I’ve given. I am also a communicator and relationship manager which I’ve displayed in the examples I’ve given you too. Analytics and data are nothing without business context, meaning and acceptance amongst stakeholders. Data science also does not occur in a vacuum; the aim of data science is to bring the right data sets together, study them and find the things that can make the customer experience better. I have shown I have the experience and skills to do this and it is the combination of all of those things that will make me the best applicant for this job.
 Donnelly, Julie A.; Altman, Reuben (1994). “The autistic savant: Recognizing and serving the gifted child with autism”. Roeper Review. 16 (4): 252–256. doi:10.1080/02783199409553591