Adam McElhinney, head of business analytics at the Chicago-based firm, told us so during last week's A2 Radio program, "How to Land a Great Analytics Job" (listen on demand). He didn't talk specifics, but the offers would appear to be enticing. Why? "We want to make sure Enova is really respected in the analytics profession and that we're driving a lot of value for the company."
Looking at the numbers, Enova typically receives a couple hundred resumes for each job it posts. If it interviews 100 people, it'll typically offer only four of them jobs -- and at least three if not all four accept, said McElhinney, who typically interviews about four to six candidates per week.
McElhinney said he thinks Enova's hiring practices and goals are what you'd find at most leading-edge analytics shops. So here are eight things you need to know if you're aiming to pass McElhinney's or his ilk's scrutiny and land a coveted analytics job.
- Avail yourself to internships. An internship, as McElhinney said is the case at Enova, "is really an extended interview process. Its purpose is a pipeline for new full-time hires." What's more, as a potential job candidate, working within a company as an intern will give you a sense of whether the environment is really the right fit for you.
- Get involved with a professional society. The emphasis here is on involvement. Don't just show up for meetings but become involved in some way -- offer up your web development skills if you have them, or help write a newsletter or volunteer to help plan an event, McElhinney said.
- Show continued development. McElhinney suggested three ways to make your resume stand out in this respect. One, get an analytics-related certification, be it via an independent organization like INFORMS, platform-specific from a vendor like SAS, or related to a specific domain, like finance, risk, or actuarial science. Two, enter a data analysis competition at Kaggle or the like. You don't have to win, but do be prepared to talk about the experience. Three, participate in open-source software development, maybe creating a package for R, working on a Python data analysis tool, or showcasing projects on GitHub.
- Be prepared for the interview. If you've neither read the job description nor researched the company, that'll be apparent during the interview -- and possibly end up excluding you from further consideration. Along the same lines, McElhinney added, make sure you can explain anything you've placed in your resume. "I mean, don't list some software package as a skill if you've only used it once and aren't prepared to talk through it extensively."
- Ask plenty of questions. It's a "huge red flag" when you don't, McElhinney said. You're potentially considering whether you want to spend your workweek with these people and build this experience into your long-term career path. "So you should have a lot of questions about the job, the culture of the company, about the backgrounds of your area coworkers, and a lot of questions about the day-to-day activities of the job."
- Don't try to be too impressive. Talking about some obscure modeling technique or software intricacy might serve to annoy more to impress, McElhinney said. Tread carefully.
- Demonstrate business savvy and be a good communicator. Having quantitative expertise is usually a given for analytics positions, but some employers are going to want you to have business acumen as well, especially if analysts are embedded in the business units. And, if you want to be in the thick of things, you've got to be able to express yourself and hold your own in presentations and conversations with the business.
- Supplement traditional analytics techniques with new skills. Today, candidates who have machine learning and programming skills stand out given the push for real-time analytics, McElhinney said. You might see this listed as data science, "but it's essentially analytics with a programming background as well."
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