It’s the eternal conundrum of a hiring manager – you have to hire for every single position in the company without any first-hand experience. How to do it? If you can have a trusted programmer sit in on the interview, that’s ideal, of course. But what if you’re hiring your first programmer? Or what if you’re hiring a freelancer? Or what if company policy dictates that you’re the only person allowed to do the interviewing? Well, in that case, you need some helpful advice and your innate bullshit detector. We questioned programmers and hiring managers and compiled a list of dos and don’ts. Here are some things to ask when interviewing programmers:

Past Experience

Ask the programmer about the biggest disaster of his career so far, and how he handled it. Did he come in at midnight to fix the code? Was he unaware of the problem until someone brought it up? Did someone else handle it?  According to our programmer sources, “Anyone worth their salt has caused a major meltdown. If they say they haven’t, they’re lying. Or very, very green.” Pushing a code with bugs in it isn’t necessarily bad. Not handling it well is bad.

As usual, your biggest asset is not knowing the field, it is knowing people. Asking about career disasters can be uncomfortable, but if the interviewee is experienced and honest then she won’t have a problem telling you about it, and you will get an idea of how she handles mishaps. Even if you don’t understand what the disaster was or how it was fixed, you should be able to tell how honest she’s being and how she handles being put on the spot.

Like me, I believe most people go about their business never to give a serious thought about their assumed private correspondence when using Gmail to email friends, colleagues and business associates.  As it turns out, your daily banter may not be so private after all.  A recent article in Fortune Magazine, “Judge Rejects Google Deal Over Email Scanning” caught my attention and an immediate thought dominated my curiosity…Google email and scanning scam.  

In essence, the article describes Googles’ agreement to change the way it scans incoming messages so that it no longer reads emails while they are in transit, but only when they are in someone's inbox! So, what exactly does that mean? Judge Koh, a San Francisco federal judge, said she's not so sure about that. Her ruling claims the settlement does not provide an adequate technical explanation of Google's workaround, which involves scanning in-transit emails for security purposes, and then later parsing them for advertising data. The judge also proposed a legal settlement to pay $2.2 million to lawyers, but nothing to consumers.

My interest in this story is not so much about the proposed settlements or the specific details about how Google or any of the web giants settle claims based on vague legal language. It is however, more about the naiveté of myself and perhaps many others that never question how the email scanning process really works. I wonder, do most of us really care that Gmail uses contents of our mail to display targeted ads?

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”

Unlike Java, Python does not have a string contains method.  Instead, use the in operator or the find method.  The in operator finds treats the string as a word list whereas the find method looks for substrings.  In the example shown below, 'is' is a substring of this but not a word by itself.  Therefore, find recoginizes 'is' in this while the in operator does not.

s = "This be a string"
if s.find("is") == -1:
    print "No 'is' here!"
else:
    print "Found 'is' in the string."
    
if "is" in s:
    print "No 'is' here!"
else:
    print "Found 'is' in the string."

#prints out the following:
Found 'is' in the string
No 'is' here!