5 Steps towards Data Science Resume

There has been a whopping 75% increase in the job postings for data science from 2015 onwards and this trend would continue to increase. While there is a huge demand and the work is also very interesting (read our mentor Sujoy’s career journey), you should be able to showcase your interest and aptitude to get that job. You need to revamp your resume, make your digital presence felt and prepare yourself for interviews. It is not easy to build a great resume, but it’s also not impossible! There are just 5 steps to build a Data Science Resume!

Step 1 : Understand the job description (JD)

Recruiters get tons of resumes for each job posting – why don’t you help them and yourself by tailoring the resume as per the job requirements? Let’s take an example of the job description for Data Scientist/ML Engineer role at Oyo.

When you look at this or for that matter all JDs, it would appear that they need you to know everything! Right from statistics to technology to communication skills to stakeholder management… and that too with just 3 years of prior experience! Well, how do you figure out what’s most important? Look at what are the responsibilities : it is essential for you to be able to design and run experiments using data, technologies and algorithms. If you could showcase a few projects where you have done this, it will be useful. Further, if the projects are related to the housing, platform or real estate business, it would be better!

It is also a good idea to find on LinkedIn what do people in these or related roles actually do! For example, look at the following samples from LinkedIn.

From the first person’s profile, you can understand what are the problems faced by Oyo. From the second person’s work experience, you can figure out how these problems could be solved!

Thus, read the JD, understand the problems, understand how these are being solved and then prepare your resume to showcase how you, with your experience, skills, techniques and business understanding, are the most suitable person they will ever find!

Step 2 : Choose the right content and structure it!

This step is quite straightforward, but most underused!

You do not have to write about all the jobs that you have done and all the projects which you have done. You do not need to show all certifications. Content which is not relevant for given JD can be skipped. For example,you should prioritize points as shown below.

If you can either mention the relevant technologies, algorithms or models as required in JD, then and only then it could be useful!

Structure your resume points to showcase the impact of the work in the most effective way. Do remember that recruiters go through hundreds of resumes – structuring helps them to scan better. Do follow the below structures to enable conveying the impact of work done and skills used!

Left to right : Mention the most important aspect of the resume point on the left.

Situation – Action – Result : Explain the context, then what action did you and hence what was the result.

For example a resume point could be:

Led a team of 6 and created 2 supply chain applications for XYZ cloud based platform
Created an intelligence tool to take supply chain decisions based on dynamic situations in real world

Step 3 : Showcase relevant projects

In case you do not have any experience and even if you do have experience, it is essential to showcase projects. Our mentor, Sujoy has mentioned the importance of projects. Do your projects on Kaggle, GitHub and do also answer to queries on StackOverflow.

Apart from Kaggle, there are several other platforms for competitions, where you may not only do awesome projects, win prizes, but also get job interviews!

Also, do mention the projects, such that you convey the business impact of the project over and above the technical details. You should also choose projects which are easy to understand and glance through. Read Peter Scobas blog to know more on choosing projects. A recruiter again does not have much time – so make it easy for her. Do this checklist before using the projects on resume.

Does it convey business impact?
Does it show collaborative skills?
Does it show ability to reason with data?
Does it show technical competence?
Is it relevant to Job Requirements?
Is it published online?
Can you explain it well?

Step 4 : Review and edit

Check for typos, spellings, facts and figures, relevance, completeness, ease of readability.
Go through your resume. Review it critically. Edit it. Repeat. Do this exercise till you think it is perfect. This step should take 30% of your resume making time, if not more ; its that important!

Step 5 : Peer review, mentor review

Once you think that the resume is perfect, get it reviewed by a peer and get it done from two types of peers. One type who have worked in data science domain and another type who do not know anything about data science. First type would give you feedback on whats missing from a data science perspective, while the second type will give you feedback from a readability perspective. Second type may not know the tools and techniques – but should surely understand business – remember that not all people in the resume shortlist supply chain would understand data science – they should understand YOU as a person!

Next, get it reviewed by an industry expert. A mentor, who has worked in the industry for a good number of years and who has recruited for their organizations. The can give their perspective as a recruiter, which is very crucial. Your resume may be stunning, but does it fulfill the recruiter’s expectations? Sujoy, our mentor and Senior Data Scientist (Best of IBM 2019), mentions :

There are two things for any data science aspirant to know. Firstly, it is important to have a resume which will make people notice you. Secondly, people will grill you on the resume – so be prepared!

All the best for your prep! Secure the guidance of a mentor here

Tagged Machine Learning