Job descriptions rarely tell the whole story
A few weeks ago, I applied for a job that was looking for a seasoned data scientist with 5+ years of experience building and testing machine learning models with scikit-learn, XGBoost and NumPy. That is pretty much what I do every day, so I was happy when they invited me to a first interview.
After that, they sent me a technical test to measure my knowledge of SQL and PySpark, neither of which was mentioned in the job description (or in my curriculum).
Five minutes into a call with the HR person, I realised that what they actually wanted was a mix of data scientist and consultant, which matched a different role on their careers page that I had not applied for.
It keeps happening
Some time ago, I applied to lead the data science team of a modern, online-only bank, only to find out that what they really needed was an expert in chatbots. On another occasion, I went to an interview for a data scientist specialised in fraud, and halfway through the conversation it became clear that they were now looking for someone with experience in risk management.
If you are job hunting and something similar has happened to you, you are in very good company.
How common is this?
A survey of 2,200 job seekers in the US, UK and Ireland, revealed that 72% of job seekers were offered a different job from the one they applied for.
Data scientists share plenty of these stories online. One candidate applied for a data scientist role at LinkedIn expecting a technical, modelling driven job, went through the SQL and data rounds, and was then told that they would be a better fit for the applied scientist role.
Why this happens so often in data science
In my experience, there are three reasons behind these mismatches.
Sometimes the people involved in the hiring don't agree on what they need, so the job description says one thing while the hiring manager has something else in mind.
Other times, the company doesn't really know what it needs. They know they want to do more with their data, so they advertise a data scientist position and work out the details as they go through the interviews.
And sometimes, what they need changes over time. The role that made sense when they wrote the ad may no longer be the priority a few weeks later, when you finally sit down for the interview.
Whichever the reason, it is rarely done with bad intent. And, these experiences say more about the hiring team than about you as a candidate.
What I'm taking from this
When a process ends because the role turned out to be something else, it tells me very little about my skills. A company that needs a PySpark expert or a chatbot specialist would have turned down the best scikit-learn practitioner in the world, so there is no point in taking it personally.
It also means that my search may take a little longer than expected. Knowing this in advance helps, because most of the frustration comes from expecting every application to be a fair match.
Next time, I'll ask the recruiter in the first call what the person in this role will do in the first six months and what the technical assessment will cover. If the answers point to a different job, I can decide early whether it is still worth my time.
Every mismatched interview still leaves me with a clearer idea of what I want and better questions for the next conversation. The right role is out there, and each of these experiences makes it easier to recognise when it shows up
To wrap up
If you are in the middle of a job search, I'd love to hear how it's going. Have you applied for a role that turned out to be something completely different once you got to the interview? Reply to this email and tell me your story, and with your permission, I might share a few of them in a future issue.
I hope this information was useful!
Wishing you a successful week ahead - see you next Monday! 👋🏻
Sole
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