Writing a cover letter for a data scientist position

This applies both to sending out application as well as contacting people in the industry. A similar elevator pitch might also be useful during the obligatory 'tell me about yourself' question during an interview.

Whenever you meet people who already work in the industry, you have to be prepared to answer the four most common questions:

• Why data science?
• Why us in particular?
• Why should we hire you? 
• What have you done before?

It is surprising how many people stumble at this stage and it is important to get this right as this could be your first impression to a potential future employer.

Creating your back story

You will need to create a compelling back story, telling them how you ended up choosing data science as a career. Whether it is at a networking event or over the phone, no one is expecting a 30 minute monologue about your childhood. All people want to hear is that you are serious about this line of work and that it is nothing you just came up with browsing a list of the 10 most hyped jobs in a magazine.

Keep these tips in mind when you're creating your back story:

• Make your back story concise and don’t ramble - you should prepare a back story that is roughly 2 minutes long for formal situations, and about 20 seconds long for more informal situations
• Make it personal but not informal - talk about any links you have into the industry or the characteristics you possess that you think would suit insurance
• Show them you’re passionate - you don't have to know everything; passion goes a long way.

To keep your story concise, follow this simple structure:

• The introduction
• The insurance spark
• Your growing interest 
• What you want to do 
• Where you want to end up

The introduction

Tell them a little bit about yourself and then which university you went to or where you started your career if you are more experienced.

The analytical spark

Most kids want to be an astronaut or an actor when they’re older, rather than an office worker.

So tell them about what sparked your interested. Be honest – if one of your friends seem to love their job in analytics, tell them. Perhaps you had a statistics class in collage and were fascinated by the methods. Maybe are a programmer that needed to analyze data in some way.

Be as specific as possible and ensure your spark is personal. Being personal creates a connection and makes you more memorable.

Your growing interest

This is your chance to show them what you have done to satisfy your interest.

Talk about the modules at university you studied as a result, or the internships you’ve completed. If you are more experienced, talk about how your past work was related to analytics and how that fueled your interest. If you are a hobbyist talk about how you started reading on the internet and downloaded programs to make your own analysis.

Mention only two points at this stage, otherwise the back story will become too lengthy.

For each of the points, say what you enjoyed and tell them about something you would like to do more of or find out more about.

What you want to do

Now you need to state what you really want to do and what brought you to them. It never hurts to play to their egos, but don’t go over the top.

Your reasons should combine your interests, your background and what you have to offer them.

A common mistake at this point is to focus in to narrowly on the technical analysis part. Talking about the whole process from data collection to business value will set you apart. Use this opportunity to tell them what you can bring to the company, whether it’s your drive, passion or Qlikview wizardry, they want to hear what you can offer them, rather than the other way around.

Move on and tell them what interests you about the company. Again, be specific. Do your research and find out details about what makes their company different and what gives them their competitive advantage (everything they are proud about will be on their website).

Where you want to be

At this point be realistic. There are only a few people who make it to the heady position of CEO and there are only certain types of people who are really cut out for it.

It is best to stick to the medium term and state you’d like to be a develop as a data scientist, and learn how to work on real data in a business setting.

Show loyalty to the industry and an interest in developing personally. That’s all there is to it.
It is best to write it down, read it out aloud and edit it until it all makes sense and takes no longer than 2 minutes.

Example: Data Scientist for an E-commerce company

“I grew up in France but my family moved to Belgium when I was twelve. I was accepted into Brussels University to study Economics and spent four years there. During my third year, I went abroad studying in China.

During my forth year I came in contact with R as an analysis software when writing my master thesis and got interested in how I could program my own analysis scripts.

After reading on the internet about 'data science' I started the Coursera mashine learning cource and become really interested to make this my career. I am not analysis expert but by now I know how to take something from an SQL database, munge the data to the right format and do regressions or charts in R.

I had previously also managed a website so I started to dig in to the data from it making graphs of what visitors were doing from the server log files. I really like the process of figuring out the answer to a question I have from data and I also enjoy the technical challenge of programming. This is something I really like to work with full time.

I know you are seeing business intelligence as an important part of you organization and I would want to learn from skilled people so I in the long term can become a better data scientist."