Six Secrets to Landing a Job in Data Science

by   |   January 3, 2017 5:30 am   |   2 Comments

Sham Mustafa, founder and CEO of Correlation One

Sham Mustafa, founder and CEO of Correlation One

If you’re considering a job in data science, you’ve picked a good time. Employers across every industry are hiring data scientists.

Here’s some more good news: You don’t need to have the title “data scientist” to land a job as one. It’s a new field, so forward-thinking employers are considering analytics professionals with a variety of backgrounds as they seek to use data to boost their business’s bottom line. McKinsey has predicted that 1.5 million more data savvy managers will be needed in the US by 2018. And the field pays well: Glassdoor reports that the national average for salaries is $113,436.

So how do you land a job in this fast-growing, intellectually stimulating, and competitive field? Let’s assume that you have the analytical skills to qualify for a job as a data scientist. Here’s how you can stand out in a pool of highly qualified applicants.

To Prepare

  1. Enhance your domain knowledge. A great data scientist has extensive domain knowledge. So whatever fields you’re interested in — healthcare, media, finance, or consumer behavior — learn as much as you can about them so that you’ll better understand the context in which you are solving problems. Domain knowledge equips you to build better predictive models and interpret data more accurately.


  1. Learn Python. Mastering a scripting language like Python is great for technical and non-technical candidates. Google has a solid applied course in Python, and there are plenty of interesting Python projects that can be found online. Better engineering skills will differentiate you from the pack, so practice coding before your interview.


  1. Brush up on theoretical fundamentals. Practice questions on probability. You should also practice hypothesis testing, Bayes’ Rule, randomization, and Simpson’s Paradox.


During the Interview

  1. Demonstrate your product knowledge. Know what the company makes or sells. Better yet, buy and use it if you can. When you’ve experienced the product or service firsthand, you can offer ways to improve it. Convey your excitement for the company, which you should have researched thoroughly, and offer insights that you gained through using the product.


  1. Ask questions. Be prepared to ask the interviewer thoughtful questions about the company’s datasets, data infrastructure, tools used by the data science teams, and the success metrics (often called key performance indicators, or KPIs) that the business uses. This demonstrates both your understanding of the business and your familiarity with the tools involved in doing the job. Your questions should reveal your passion and curiosity about data science.


  1. Offer examples of communication and storytelling about data. Show your interviewer that you can communicate with a technical as well as a non-technical audience. Don’t assume the person who is interviewing you has technical expertise. If she comes from Human Resources or Marketing she may not have technical skills even though she may be a senior manager. Decision makers who aren’t technologically-savvy often prefer to hire people who can avoid jargon and who are able to tell a story from the data.


After the Interview

No matter what kind of job you’re applying for, after each interview, write a thank you note to the person who interviewed you, and be sure to include any follow-up information your interviewer requested. Perhaps most importantly, use the note as one more opportunity to convey your enthusiasm for the position!

Remember that attitude is half the battle, so keep it in mind before, during, and after the interview. Be optimistic and focus on the positives of the positions that you consider. Always be friendly, be polite, and be yourself — not just in person, but over the phone and email too. You’ll likely have some setbacks as you pursue your next opportunity, and that’s okay. Nothing is a waste, and everything can be a learning opportunity. With a little preparation and an interview performance showcasing your technical know-how, you’ll be well on your way to beginning your career in data science.


Sham Mustafa is the founder and CEO of Correlation One, a data science marketplace. Prior to launching Correlation One, Sham directed operations at two specialty finance firms. He holds an MBA from Columbia New York City. Mustafa has provided business advisory services to more than 600 small business schools, an MPA from Columbia University’s School of International and Public Affairs and a BA & LLB from the University of Madras, India.


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  1. S Don
    Posted January 4, 2017 at 11:51 am | Permalink

    This is a great article refreshing the basics of landing a job. Apart from the things that we need to learn for a job in data science I particularly liked the way you have stressed that having good attitude is more important. Reading this article was a great way to start the day.

  2. Anjolaiya Oladipo
    Posted January 6, 2017 at 2:41 pm | Permalink

    This information is quite refreshing and energizing. Most especially as it addresses the key guidelines and blue prints to landing a job as a data scientist. As a young and aspiring data scientist i hope i can also imbibe these sets of instruction in improving myself and adding more value…The stats revealed in the article further convinces me about the future prospects of my passion in becoming a business intelligence and data wizard…Thank you so much sham…

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