So Your Company Wants You to Start Interviewing

    Image by Makyzz I finally have a reason to say: these opinions are mine own and not my employer’s ;) I’ve chosen to frame things with my current employer in mind because after three years the bulk of my interviewing experience and experiments have been with them, but really this is just my opinion on how technical interviews should be, not an accurate description of how USDS interviews. I’ve gotten a couple of requests for this post. Technical interviews have become one of my favorite topics to wax poetically about over the last few years. Most people who either encounter me in person or frequent the same online communities as I do have been treated to the output of some of my experiments in different approaches and types of questions. Some have even become guinea pigs for them. My fascination with this topic started when I interviewed for the job I have now. Because it was bad. It was very very bad (although in fairness the organization was barely a year old by that point and scaling up faster than sensible process could be built). It was so bad that my second week on the job I was asked to help fix it — my second week! Here’s what happened: no one asked me any programming questions of any kind. It was pretty weird. I had what I could identify as a basic technical screen that asked me a lot of stuff about the Linux command line and TCP/IP, then I had another interview where I chatted about my resume, then I had an interview to assess my emotional intelligence where the interviewer threw out the script the organization used and we talked about legacy software and using computer vision to sort a backlog of scanned medical records (specifically how to design an algorithm to classify MRIs, X-Rays, and CAT scans). It was pretty weird for a couple of different reasons. First of all, the vast majority of my resume talked about my experience with data infrastructure and no one ever validated that. Not one question about databases or API design or ETL pipelines or anything of the kind. Then there was the fact that the screening questions were heavily biased toward Linux and when I arrived all the computers I worked with were (at the time) Windows machines. And of course, they were hiring me as a software engineer and no one had looked at a single line of code I had written. When I started work a few months later, I realized that internally the organization was just as frustrated with the process as I had been. I got pulled into the effort to design a better system, which scared the crap out of me. Sure, I had interviewed people before. I had hired people. I had fired people. Just not on the scale that USDS was looking for, not with the level of process and consistency that USDS expected. I ended up learning a lot and it was tremendously rewarding to help make a tiny, fragile organization stronger. (It still is) TL;DR: Rules for Constructing an Interview This will be kind of a long post. I’ll reference some theory, but I’d really like to be more specific and pragmatic than most reference guides on this topic usually are. But essentially my philosophy about interviewing can be broken down into four basic rules: 1 — We ask questions that reveal who we are, what we value and what is exciting about our work. 2 — We ask questions that test skills we actually need and have been vetted for false correlations (for example, knowing the appropriate order of arguments for a command or function off the top of your head indicates a good memory, not necessarily superior programming ability). 3 — Our process is standardized in such a way that the candidate would get an equivalent experience from any of our interviewers, but allows enough flexibility for interviewers to dig into details specific to just that candidate and her answers. 4 — Our interviews are structured in such a way that different perspectives increase the strength of the signal, not the noise. Rule 1: YOU Are Not Interviewing THEM Interviews, especially technical ones, are bi-directional. You are trying to ask questions of candidates that help you figure out whether it’s worth hiring them, but they are also assessing whether your organization is a good fit for their needs. Before my last interview I had absolutely no intention of coming to USDS. I nearly missed out on my dream job because none of the interviews that came before that last one actually reflected what the work was. They asked me about technology that is common and popular but not used in government. They asked me about concepts too basic to reveal what their needs were. They did not verify my skills which suggested to me they did not think my skills were particularly valuable. Then the last interviewer threw out the script and asked me for advice on what he was working on. In doing so he gave me a guided tour of his day-to-day. I found it fascinating and I was hooked. Candidate experience is an under-appreciated and under-invested component of interviewing. Too often candidate experience is thought to be the responsibility of Recruiting or HR, but first and foremost as an interviewer you should be designing your interviewing strategy around giving every candidate, regardless of their level of talent, a great experience. Do not fall into the trap of thinking that a harder, more grueling interview is a better interview. If you are putting a candidate through hell because the job is stressful and you want to test their ability to handle that stress, the candidate should be able to tell that is the purpose. If you are putting a candidate through hell just to put them through hell, then what the candidate learns about your organization is that it is a place where assholes are allow to thrive. A hard interview isn’t always an unpleasant interview either. It’s all about purpose. That last interview for USDS forced me to talk about computer vision, something I had no experience implementing. Sure I understood the theory, I knew some of the toolsets, some of the research, but I could not really speak with authority on how one would implement such a solution because I never had. Despite that I found this conversation fully engaging because it was obvious that what the question was testing had nothing to do with computer vision or even machine learning. The interviewer started out by giving me a broad picture of the problem. Every time I came up with a solution he would add some complication. Computer vision was where we ended up, but what the question was actually testing was my resilience and creativity. Since that was understood, the fact that the interview pushed me to the limits of my knowledge was not an unpleasant experience. I left that conversation feeling awesome. But thinking about what interview questions say about your organization -vs- what their answers might say about your candidates is not something most interviewers spend a lot of time on. Consider the following question (note that none of the example questions here are actual USDS interview questions, sorry) The CISO at the Department of Technology is forbidding the use of Google Chrome on government computers bought and provided by his Department. His team are required to test and scan every software update before it’s allowed to be installed on a Federal network and he thinks that Chrome releases too many updates, overloading his staff and driving up cost. He would like to require all Department employees to use Internet Explorer so that his team need only vet one set of updates. How would you advise him? So starting off, does this question accurately describe the challenges my organization faces? Unfortunately, yes. Although this specific situation has never happened, we have encountered the individual elements. Some agencies do turn off autoupdate on software like Chrome so that they can evaluate and approve every update themselves. Some agencies do require use of Internet Explorer (usually because they are using some obscure plugin only supported by IE). Cost is a critical factor in decision making at all agencies. Does this question accurately reflect what we value? Yes. The wording of it suggests that we disapprove of the scenario and the reasoning leading up to it. We could have worded this question in a more neutral way to allow people to argue in favor of the CISO’s strategy, but instead we give them a little more information about who we are. Does this question help us assess a candidate’s fit for our organization? Yes, in a couple of different ways. Some candidates may not think they can push back on the CISO’s plan in its entirety and may end up trying to figure out how to implement IE-only. Some candidates will try to dissuade the CISO diplomatically. Some much less diplomatically. We’ll end up learning not just about the candidate’s technical ability but her temperament, patience, ability to explain technical concepts to various audiences … all good data points for us in determining whether someone will succeed here. But here’s the problem with this question: does this question reflect the work we want to do? No. Is it a problem that an engineer is going to get excited about solving? Probably not. We might get a lot of good data from this question, but we ultimately give the candidate a negative impression of what it’s like to work for us. Like most organizations, we don’t want to invest time and energy interviewing people who do not accept our offer when made and if a candidate ends up thinking to herself “God this work sounds awful!” because we’re asking her things that don’t reflect our best work then that’s exactly what will happen. Let’s look at another hypothetical question: An important application that processes visas is down. Embassies and consulates around the world are panicking as their visa operations grind to a halt. Meanwhile farmers in the southern states are facing a shortage of help with thousands of migrant workers unable to cross the border for the harvest. The application is written in Java with an Oracle database. It is hosted in a private government data center located somewhere in West Virginia. The servers are Windows NT 4.0. The outage appears to have started over the weekend. How would you begin diagnosing and resolving this issue? Does this question accurately describe the challenges my organization faces? Yes, USDS was founded to handle situations like the one described above. Does this question accurately reflect what we value? Yes. There’s no reason to include the background information about farmers and migrant workers except to tell the candidate that we do work that affects millions of real Americans. Does this question help us assess a candidate’s fit for our organization? Yes. Does this question reflect the work we want to do? Yes! So the second question is probably better, but the first question may not be a bad thing to ask if it’s part of an overall strategy. In other words, if you have other questions that better represent what is compelling about your work and you want to gather data on the candidate’s tolerance for some of the tougher challenges … that’s a fair thing to test for. Rule 2: Know What You’re Testing Perhaps the biggest problem with technical interviews is that they may not test for the skills you’re actually hiring for. There are no neutral interview questions. All interview questions favor a certain type of experience, a certain type of person, or a certain stage of a candidate’s career. If you’re asking questions that match the type of people you are looking to hire then the bias is acceptable. If you’re asking questions that favor characteristics contrary to your needs then the interview will not be able to produce consistent and clear data. In the absence of good reliable signal, hiring decisions get made based on more pervasive and destructive biases (like gender, race, age, and other “culture fit” criteria). Here are some common interview formats and the types of people they are biased towards: Algorithm puzzles: new grads over-perform, seasoned professionals under-perform Brain teasers (ie — “how many jelly beans fit in a VW bug?”): People with anxiety issues under-perform, also tends to alienate strong candidates. Coding challenges: biased towards particular languages, rewards hyper-optimization. Obviously, asking questions that are easier for new grads to answer is not a problem if what you want are bright young new grads. Similarly if you are a Ruby shop, coding challenges that set non-Ruby programmers at a disadvantage is not necessarily a bad thing. Something we have struggled with at USDS is how to accurately assess someone’s programming ability when the stack could be almost anything. I have pretty vivid memories of walking into USDS HQ one evening to find one of our more experienced interviewers flapping around in panic while obviously in the middle of a phone screen. Once I confirmed the phone was on mute I asked him what the problem was. “I told him he could do the exercise in any language and he chose Haskell! Do you know any Haskell?” (answer: a little, but only because Evie Borthwick talked my ear off about it for roughly two years) We do our best with it, but it remains a challenge. When I was planning out the interviewing strategy for TRU, I decided I was less interested in code writing and much more interested in code reading. I wanted to assess the candidate’s ability to take something completely foreign and start to break it apart. I ended up writing the following question:


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