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Gold BlogA Step-by-Step Guide to Transitioning your Career to Data Science – Part 1


If you are looking to transition your career to data science, don't immediately start learning Python or R. Instead, leverage the domain expertise you have accumulated over the years. Here's a foolproof guide on how to do that.



Step by step guide to getting a job in data science

If you are looking to transition your career to data science, the most common advice you may have heard is to learn Python or R, or to learn machine learning by pursuing courses like Andrew Ng's ML course on Coursera, or to start learning big data technologies like Spark and Hadoop.

I call this a technology-focused route to a data science career.

This approach makes complete sense if you are a programmer or if you have a Ph.D. If you are coming from a non-technical background the easiest way to get started in data science is to take a domain knowledge focused approach.

If you look at Drew Conway's Venn Diagram, you will notice that a data scientist doesn't just possess technical skills. They also have domain expertise.

data science venn diagram

So, why not leverage it? I always believe in playing to your strengths.

Let me explain this approach in detail.

Step one: Discover your dream job

Data science is used in several domain areas (such as marketing, finance, HR, etc) to solve interesting business problems.

Your first step is to choose a data science job title within your domain.

Let me illustrate this with an example.

I will assume that I am a digital marketer looking to transition to data science. If I Google “marketing data science jobs”, I get a list of job postings with the following titles:

  • “Senior marketing data analyst”
  • “Senior data scientist - marketing”
  • “Marketing analytics specialist”

I then go through each description to understand which of these job titles closely match my current skills (in terms of domain knowledge).

By doing this exercise, I find out that "Marketing Data Analyst" role is a good fit for me. I also discard senior roles because they need prior experience in data science - so they won't be good targets.

Here's a Marketing Data Analyst job description:

marketing data analyst - job description
A strong candidate for this job role will have decent Google Analytics skills, understands online metrics (such as visits, conversion rates, etc), and should know how to perform campaign analysis. If I am a digital marketer who has these skills then I am a strong candidate for this role.

Here are the technical skills listed in the job description:

marketing data analyst technical skills

In this stage, I am not going to worry about the technical and analytical skills listed in the job description because my focus is only on domain knowledge.

You can apply the same principle to choose a job title to target within your domain area.

Once you have decided your target job role, it’s time to shortlist your target companies.

Step 2: Discover your dream company

You have to shortlist 5 companies to target using one of these two criteria:

  • They frequently advertise your target job title.
  • There are a good number of people who have your target job title.

I have found companies that mostly hire data science professionals usually fall within one of these categories:

  • Mid-sized tech firms
  • Boutique data science consulting firms
  • Big consulting companies
  • Major Financial institutions
  • Big retail firms

It is pretty difficult to get an entry-level data science job in major tech companies (such as Facebook, Google or Amazon) so don't target them.

For my "Marketing Data Analyst" role, I have shortlisted top 5 banks in Canada:

  • TD Bank
  • RBC
  • CIBC
  • BMO
  • Scotiabank

Step 3: Network with right people

You've picked a target job role and a few companies. You've done your homework. But there's only so much you can do from your room.

You still have lots of questions, like:

Can I actually get this job?

What should I do next?

How do you answer these questions?

By testing.

Except this time, you'll talk to real people: the ones who have already been there before.

Here are the steps that you can follow:

  1. Find people who have your target job title at your shortlisted companies
  2. Email them and for either a coffee meeting or a phone call.
  3. Show up and ask good questions.
  4. Follow up and build real relationships.

The first step is to use LinkedIn to find at-least 2 people who already have your target job title at each of your target company.

In my case, I will type "Marketing Data Analysts TD Bank” in the LinkedIn search bar to get my target list of people in TD Bank.

If they have 500+ connections on LinkedIn,  I will then contact them via LinkedIn or else I will contact them via email.

You can use a tool called “Voila Norbert” to get their official email id.  You just need to enter their name and the domain name of their organization in this tool to get their email id.

You can use some of these templates to get in touch with your contacts:

Initial LinkedIn request message:

I was doing some research on Marketing Data Analyst positions on LinkedIn, and I noticed you're a Marketing Data Analyst at [company name]. Your career path is very inspirational to me. I'm on a quest for my dream job and would love to ask you 3-5 questions about your career path.

Once they accept your LinkedIn request:

Thank you for accepting my request.

My name is [name], and [a few words about you].

As I said before, I'm on a quest for my dream job ([Your Target Job Title]) and would love to ask you 3-5 questions about your experience at [company name].

Your insights would be helpful for me. I will be in town from Friday (14th Sep) to Monday (17th Sep). Would you be available for a quick chat over coffee anytime from 14th September to 17th September?

You can use the above LinkedIn message as your first contact email, with the following subject line:

Aspiring data scientist — looking for advice from the best

If you don’t hear back from them after 3 days, then send a follow-up email like this:

 I wanted to follow up on my previous message.

 At this point, I have:

  •  Decided the job title that I am going after: marketing data analyst
  • And a list of companies I am interested in applying to, also thoroughly researched them.

I do have few questions regarding my approach – that’s why I am reaching out to experts like you (who already possess my dream job).

I strongly believe that your guidance and feedback on my approach to data science job market would help me a lot.

Again, if you don’t hear back from them after 2 working days, send one more follow up email:

Hi [name], I wanted to reach out one last time on my previous message. If I don’t hear back from you, I’ll  assume the timing isn’t right. Your guidance would help me a lot in the pursuit of my dream job journey.

Before you contact any of your targets, see if you know someone who can introduce you to them. It can be your college alumni or your ex-colleague.

You can also use a simple excel sheet to keep track of this entire process. Here’s an example:

sample excel sheet to track email progress

Assuming one of your target prospects say yes, let's talk about what to do at that actual meeting.

Remember that these Informal meetings are for you to test your ideas and gain new insights. They are NOT to get hooked up with a job. Never ask for one here. You are in the research phase. Right now you're just gathering information. They're also not to talk about yourself, so kindly listen. Your job is to learn here, not to talk about yourself.

If you have a half-hour meeting, you should spend approximately 25 minutes asking them questions. In the last five minutes, you can spend a few minutes talking about yourself.

Try to ask smart questions. You try to answer each question yourself before you actually ask it. Scenario-plan each answer out.

Here are some questions you can ask:

  • I would like here your story on how you started your career in data science
  • Can you tell how data science adds value to [company name]? Some examples of recent work?
  • What software and machine learning techniques does the team at [company name] use regularly?
  • Typical background of the team?
  • Does [company name] hire people without previous experience in data science?
  • If so, what important skills and characteristics do they look for in a candidate who doesn’t have previous experience in this field?
  • If I applied to [company name], what do you think would make me stand out? If I had an interview next week, what kind of advice would you recommend to me?

After the meeting, send them a thank you email the same day.

Just wanted to thank you again for meeting with me yesterday - it was incredibly helpful.

I think my next steps are [Include a few things from your conversation].

Please let me know if there's anything I can do to repay the favor!

You should meet at-least 2 people at your target company.

Till now, you've had ten coffee meetings and have answers to all your questions. What you do with all these answers? How do you convince the people you have met that you are a strong candidate?

That’s exactly what I’m going to talk about in my next blog post. Stay tuned.

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