Revealed: What hiring managers look for in data scientist CVs

This week in Tech in Asia Jobs shares insights into how successful companies operate, hire, and more.

Photo credit: stockasso / 123RF Stock Photo.

I’ve just completed my first round of recruitment since joining Royal Mail as their first head of data science, with some successful candidates joining my team. But having been involved in hiring data scientists for many years now, I still find myself wishing too often that the information I’m looking for was in the CV in front of me. It just seems like data scientists, in general, don’t know what they should put in their CVs, as they don’t know what hiring managers are looking for. And this leaves hiring managers like me with the dilemma of either rejecting most of the CVs (and taking the large risk of dismissing some potentially very good candidates) or employing an additional telephone screening stage to get more information from potential candidates.

Neither scenario is ideal and both have their pros and cons. So I thought I would try something different and instead write down what I would like to see in an ideal CV from a data scientist applicant. My hope is that this will start an interesting discussion and help me further improve my recruitment process. Ultimately, I also hope this results in improving the quality of CVs across the data science community and help me to streamline my recruitment process.

Educational background

The first thing I look for in a data scientist’s CV is evidence of a solid educational background in a heavily mathematical subject. Almost anyone can claim to be a data scientist these days just because they know how to use machine learning to build you a solution to your problem. But to me, a real data scientist is someone who understands the technical details behind the algorithms and knows what assumptions they are making when using one algorithm vs another. This tells me that they would select the right algorithm for each specific problem and will be able to engineer the most appropriate features for that algorithm.

Therefore, I would like to see an externally validated qualification, such as a university degree or equivalent, and I’d like to see this on the first page (at least mentioned in the personal statement at the start).

Independent research experience

Data science is, by definition, a research activity, where we are always looking to solve a problem where the solution is not obvious and success is not guaranteed. Otherwise, we are not doing real data science! This is why I’ve taken Eric Ries’ Lean Startup framework for innovating in the midst of a lot of uncertainty and adapted it to make it work for data science. And thus, I’m running my team at Royal Mail as a lean startup.

So I’m looking for some evidence in the CV to convince me that the candidate is capable of carrying out independent research. The most obvious evidence for this would be a PhD or at least an MSc that included a research project.

The biggest mistake candidates make in this area is to just say they’ve done an MSc or a PhD in some specific subject (e.g. MSc in computer science or a PhD in statistics), and possibly mention the university. But what I really want to know are the details of their research activity and how successful it was; I’m more interested in the title and summary of their thesis. If the work was novel and successful, it would give me confidence in their ability to carry out independent research. But of course, attaching their thesis to their CV is not the answer. In fact, their ability to summarize the key aspects (context, approach, outcomes, and novelty) of their research activity in one paragraph is a very important indicator of their written communication skills as well.

I would also consider alternative equivalent research experience (e.g. experience as a research scientist or data scientist). But in this case, it should ideally be called out in the personal statement and the examples of research projects described in the relevant section of the CV (e.g. in the work experience section).

Programming skills

Next, I’m looking for evidence of the candidate’s programming skills. Some candidates love to list 101 languages, thinking that it makes them look really attractive. But in reality, they would only use two or three languages on a regular basis. The key for a hiring manager is to see that the candidate has experience in at least one language of each of the following types:

1. A high-level rapid prototyping language such as Python or R
2. A low-level deployment language such as Java, C++, C#, etc.
3. A scalable/big data language such as Scala/Spark

I would want to see all three for a senior data scientist, the first two for a data scientist, and just the first (R or Python) for a junior data scientist.

The other mistake I see in CVs is just having a list of programming languages with no indication of proficiency or experience. The really good CVs not only list the languages along with the number of years’ experience in brackets (e.g. Java [6+ years]) but also list the languages used in each data science project they mention in the work experience section.

Impact, impact, impact!

Coaching, mentoring, and line management experience

Technical breadth and depth

Tools and processes

An open mindset

Soft skills

Summary