5 Job Hunting Tips for Female Data Scientists

By Mısra Turp, Business Owner at So you want to be a data scientist

Guest post by Mısra Turp, Business Owner at So you want to be a data scientist.

Changing jobs is stressful. But it doesn’t have to be. By following some simple tips, you can make sure you are on the right track and will be happy in your new position.

In this article, I will break down my decision process while searching for, finding and applying to a new job, to help you with your job search.

Some background

At the beginning of my career, I was in a consultancy position. I realised in time that even though I liked being involved in a variety of projects which were in a variety of industries, I was not happy. I had two reasons to be unhappy: I was not ambitious to grow into the direction the consultancy role provided me and I was not happy with the amount of impact I had in the world.

After this realisation, my first reaction was to go on LinkedIn and similar websites to look for open positions. After a while, I got nowhere. I was not feeling good about my job search and I felt like I wasn't making any progress. This was when I realised that I needed a structured approach.

Tip #1: Find your “why”?

My main reason for leaving was that I didn’t have any ambition to climb the corporate career ladder and that the projects did not fulfil me. But when I started looking for jobs, I again ended up applying to places where I know the situation would be very similar. I simply forgot that what I wanted to do was not to “leave as soon as possible”, it was to “find a more suitable position for my needs and wants”. 

This is a mistake many people make while looking for a job. Just make sure to remember why you got into this search in the first place, remember your priorities and do not stretch them too far.

Tip #2: Determine your priorities

If the reason you want to become a data scientist is to work with Machine Learning, do not apply for a job that might have you working on simple dashboard building just because the title is “data scientist”. Your energy is much better spent on applying to places that are good for you.

To achieve this, you need to have your priorities written down. First the must-haves:

  • I want to have a positive impact on people’s lives

And then the good-to-haves:

  • I want to work in healthcare or a related industry
  • I want a team that I can learn from
  • I want to be challenged 
  • I want to have multiple responsibilities and not just data crunching
  • I want a smaller company where things are not very bureaucratic

Tip #3: Reach out to the community

After writing down your priorities, it’s time to do some research. Look around you and find people who work in positions/companies you envy. Ask them if you can talk to them and hear their stories of how they got where they are, what advice they can give you on the next steps. You will learn so much about how to approach your specific job search this way. 

I talked to a bunch of people but the most helpful was the founder of a social enterprise and one of the guests I had on my podcast. We had a chat about what I want, why I want it and how I can use my skills (data science skills in this case) in a social enterprise or non-profit. This conversation saved me so much time and energy because it confirmed my suspicions about entering the non-profit scene. Thus, I focused more on for-profit organizations.

Tip #4: Be true to yourself

I believe that the only way to find a place where you can be happy is by showing your true colours as much as you can at the beginning. If you can’t identify with a company’s tone, character or vibe, there is very little reason to try to be a part of it. Almost certainly you won’t feel like you belong there when you start.

To evaluate this, you can identify companies that fit your must-haves and good-to-haves profile and reach out to them. The key here is to keep the conversation on a very honest level. Do your best being yourself. Don't send a cookie-cutter introduction message praising yourself for perfectionism. Take the chance to go all-in with where you are in your career, what you want and how they can help you.

When I was doing this research, I knew I wanted to work at a place where I don’t have to pose like a perfect professional worker, so I made sure my emails and messages did not sound corporate. And the magic happens when the company you’re applying to replies in the same tone. That’s when you know you get a match. 

Tip #5: Evaluate the fit objectively

The last step of job search is to evaluate your options. As I mentioned before in another article, asking questions during an interview is a great idea. This is not only to show that you are interested. It is important information for you to understand what I was getting myself into. 

While preparing your questions, keep your must-haves and good-to-haves in mind. Some things you can ask for are:

  • the main mission of the company, 
  • the culture, 
  • the size of the company/team, 
  • what their business model is (as in how do they make money), 
  • what will be expected of you 

and so on… This is important information for you to make your final decision on whether to go forward with the company or keep looking.

Bonus tip: Realize your own value

I talked to a lot of female data scientists on my podcast. All in great positions in awesome companies. Yet while talking to them about how they got to where they are, it always sounds like they think they got lucky.

I believe although it's nice to be humble and not brag about how superb you are, you need to own your achievements.

I don't believe in getting lucky when looking for a job. It's every person's achievement. There might be a lucky situation you found yourself in but you have brought yourself up to a certain standard to be able to take advantage of this opportunity when it arose. Own your value and be aware of your strengths. Confidence and awareness might make all the difference in a job hunt.

Hope these tips will help steer your job hunt in the right direction. Don't forget to be honest to yourself, every step of the way.

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