Here are 10 tips that I have for aspired data scientists which come from my experiences of applying for data science roles and participating in the recruitment of other data scientists.

1. Show how your past data science experiences added business value

Do not write things like this, “Automated logistic regression model to speed up loan conversions”.

Phrase it like this, “Automated logistic regression model to increase loan conversion by 34% and increase originations by $12million”. This tells the recruiter that your knowledge of a simple machine learning model had direct and positive business impact.

2. Do not only list technical skills!

Ambiguously listing skills can make recruiters skeptical. State how they’ve been used in your past experiences.

3. Know your statistical concepts from a business perspective

Some examples of topics that I have been asked in interviews are distributions, minimizing loss functions, generalized linear models, cross validation, experimental design, and model performance metrics.

I found that the best candidates actually knew how these concepts applied to real-world business problems. You can tell who went through trials and tribulations of deciding how to build statistical models by the way they have reasoned with business problems.

  • Why did you choose to optimize the AUC instead of Accuracy?
  • Is removing a set of complex features in your model worth the accuracy decrease if it means saving on computation?
  • How have your stakeholders responded to the data science product you have built?

4. Prepare to code, solve a problem, or work on a case-study!

This is to show that you can do exactly what you have claimed your abilities to be. These usually come in the form of problems that test your conceptual knowledge from academic studies, or to simply see if you can perform simple tasks. It is also an opportunity for recruiters to see how you think. Do not be afraid to think out loud!

5. Focus on data science business value and not technical jargon

During interviews, I cannot emphasize enough how important it is to be able to articulate how your data science experiences gave value without getting lost in the technical explanations.

6. Prepare to simply explain complex technical concepts

Non-technical and technical audiences always appreciate a level of sophistication and simplified communication.

7. Ask about the firm’s plan on using data science in the long-term

Data science is still a newly hyped field and many firms are still riding the wave of introducing it to their business.

A major red flag is if the company does not list strategies of using machine learning or artificial intelligence within their business, service or product. This is important especially if you seek to engage in data science projects early.

8. Ask about the firm’s data science expertise, and reporting hierarchy

Will you be working with other data scientists? Will you be reporting to someone who is experienced in data science? It is so important that you ask these questions as they relate to your career growth and work relationships.

In the past, I found it very rewarding in my career to report to someone who was very knowledgeable and experienced in data science. I have also found it rewarding to be the only subject matter expert. Figure out how you view yourself as a data scientist!

9. Confidently admit gaps in your knowledge

Admitting gaps in knowledge and explaining how to cover weaknesses may show recruiters that you don’t know everything. You need to show that you have the drive and passion to learn.

10. Learn your niche and ask about future growth opportunities

You do not need to be a data scientist forever. Data scientists build skills that are transferable to other roles such as software engineering, product management, team management and business intelligence.

Whether you’re starting on your career or a seasoned data scientist, it is important to know what you’re good at so that you can focus on improving in other aspects of your skill set.

What advice or tips do you have for prospective data scientists? What has worked for you in your data science job hunting journey?


For more guidance on data science resume building, you should definitely check out this thorough actionable guide on Data Science Resume Tips!

Don’t forget to check out my blog post on my data science job search history which inspired me to write these resume and interview tips!