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Whether you have recently graduated or taking a break to upgrade your skills or making a career shift, you need to have the right resume to get the right job!
Resume building is the crucial first step to get your foot in the door and open up a dialogue with the recruiter. And to do that you need to demonstrate that you possess the right skills for the job you are applying for. The recruiter’s job is to find the best person to fit the job.
Why do you need a great resume?
Your resume is a critical job search tool. It is your first impression with employers. It is one of the few things in your life that needs to be absolutely perfect. You will be competing with hundreds of other resumes, hence your resume will need every edge it can get. Your resume is the physical representation of your achievements, and it should motivate the person reading it to invite you for a discussion.
What is a resume?
A resume is a written compilation of your education, work experience, credentials, and accomplishments. It is a document that summarizes your career history, skills and education.
A resume is your professional highlight reel – presented in an easily understood and standardized format. A resume is typically limited to one or two pages of size A4 or letter-size, highlighting only those experiences and qualifications that the author considers most relevant to the desired position Resumes can vary in style and length, but should always contain the accurate contact information of the job seeker.
Which type of resume is best for you depends on the situation!
For each job application, choose the format that best represents you in the context of the job you’re applying for. The most common format is the chronological resume, which happens to be most preferred by employers.
The Ten Commandments
- Be Concise, Less is More
- Your resume needs to show that you’re the best fit for the position. It should be concise, crisp and appealing. It should not be an extensive list of everything you have ever done. You need to have enough relevant and important experience, training, and credentials to showcase.
- Think of your resume, not as a comprehensive list of your career history, but as a marketing document selling you as ‘the perfect person for the job’. A good resume should only be one page long unless you have 15+ years of relevant experience for the job you’re applying to.
“Before I meet somebody, the time that I spend [on each resume] is less than 30 seconds. If that resume doesn’t speak to me, which only happens with one in ten resumes anyway, I’m not even going to call the candidate.” – says Stephen Yu, president and chief consultant at data analytics consulting firm Willow Data Strategy.
2. Make your contact info Prominent
- Your name – located at the top of the page should be the most prominent visual element on your resume. Font size for your name should be at least 2 points larger than the normal font.
- Make sure you include a phone number and professional email address as well as other places the hiring manager can find you on the web, like your LinkedIn profile and Twitter handle.
- A good email would be some combination of your first and last name, i.e. [email protected] or [email protected] You should not use a personal-looking email address like [email protected] or [email protected] on a resume. Also, use a URL shortener for your LinkedIn profile link & do not just copy-paste the entire URL.
3. Highlight your education, not your GPA
Highlight your education at first on your resume only if you’re a graduating student looking for the first job in a relevant field. Many resume templates list education first, but only if you’ve got work experience and/or relevant projects to showcase, you’ll want to show those off first and put education closer to the bottom. E.g.:
4. Reflect the language used in the target ‘ Job Description’
The keywords and the theme that you see in your target job description will form the foundation of the achievements you will highlight in your resume to demonstrate your suitability for the role.
For e.g.: Statistics, Data Mining, Machine Learning techniques, Data Visualization, Classifiers, Anomaly Detection, WEKA, Numpy, Matlab, Visualisation, D3.Js, HIVE, Ensemble, Nosql, Databases, MongoDB, Hbase, Business Insights, Highly Analytical, Interpreting Data.
5. Keep it recent, keep it relevant
You should only show the most recent experiences of your career history and only include the relevant experience to the position you are applying for.
For those of you who do not have any experience, please focus your resume on your relevant skills along with data science academic projects and internships.
It is crucial that you use strong, energetic language to highlight your accomplishments in your experience. It is best not to use a lot of industry jargon so that your resume is understandable to the average person (the HR here who is not a technical person most of the time). Remember that the first person who sees your resume might be a recruiter, an assistant, or even a high-level executive—and you should be sure that it is readable, relevant, and interesting to all of them.
6. Curate your bullet points
Have not more than four or five bullet points, no matter how long you’ve been in a job, or how much you’ve accomplished there, in a given section.
The recruiter might just not have the time to go through them. Bullet points should be in the order of relevance, relativity and results-oriented.
“If a recruiter is going to read a resume that’s more than one page, it is better to tell a good story about what you bring to the table. Listing every task you did as a manager doesn’t make you a good manager. But if you tell that you increased productivity by 25% or highlight process changes for multiple teams at several companies—you’re justifying that space.” Says Yolanda M. Owens, a recruiting specialist & award-winning author.
7. Avoid Empty Words
Detail-oriented, team player and a hard worker are among a few vague terms that recruiters say are chronically overused. Some of the worst resume terms used are- Go-getter, out-of-the-box thinker,results-driven, team player, hard worker, strategic thinker, detail-oriented.
Best resume terms: Achieved, Improved, Trained/mentored, Managed, Created, Influenced, Launched, Developed, Applied, Conducted, Solved, Created.
- Created machine learning models with Python and scikit-learn to predict energy usage of commercial buildings with 98% accuracy.
- Developed an algorithm in R that automated financial forecasting.
Make sure your resume is free and clear of typos. And don’t rely on spell check and grammar check alone-read it again & again. According to a survey, 61% of recruiters reject resumes with typo errors.
9. Save it smartly
While emailing your resume, make sure to always send a PDF rather than a word document. That way all of your careful formattings won’t accidentally get messed up (which generally does happen) when the hiring manager opens it on his or her device.
Save it as “Robert_Downey_Resume” instead of “Resume.” Or “ABCXYZ Resume” or full names. It’s one less step the hiring manager has to take.
10. Constantly refresh your resume
Carve out some time every month/quarter or so to pull up your resume and make some updates. Have you taken on new responsibilities? or Learnt any new skills? Add them in.
“Do not include any kind of technical skills that you have not worked with.”
You certainly can create a single resume and send that to every job you apply for, but it would also be a good idea to try and add customized tweaks to your resume for each application you submit (only if you are hands-on with those skills). This doesn’t necessarily mean you need to do a wholesale rewrite and redesign every time you apply for a job!
But, at a minimum, if you notice important keywords and skills mentioned in the job posting, make sure the resume you’re sending highlights your skills in those areas and makes use of those keywords only if you possess the right skill sets demanded by the job. For e.g.,
a) For a Machine Learning Engineer role, you can mention skills like Probability & Stats, Programming languages like Python/C++/R/Java, Data Modelling & Evaluation, ML Algorithms, Distributed Computing, Advanced Signal Processing Techniques.
b) For a Data Scientist role, you can mention skills like Python/R/SQL, Tableau, Hadoop, Stats, Data Visualization, Deep Learning, ML, Neural Networks, NLP.
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