If you missed Part One, you can find it here.
Part Two of this blog will go into more detail about how to best highlight your skills and experience in your resume and/or LinkedIn profile. The key to a good Data Science/Analytics resume is to be succinct and direct. If you’re going to be good at your job – you’re probably going to have to do a lot of complicated technical work and then summarise it so that even non-technical people can understand it.
The format I love seeing is: contact details, education, technical skills (primary and secondary) and then into work experience.
Contact details: include your name, email address, mobile number, LinkedIn account and suburb. Unlike other countries, there is no need to include your “personal” details such as age, gender, marital status or a photo of yourself.
Education: include where, when, what degree, and your GPA (if it was a distinction average or above).
Technical skills: include 3-4 “primary” technologies/languages and a maximum of 5-6 “secondary” languages. Base this on frequency of use, confidence and relevance to the role.
Work experience: include your job title, company name, duration of the role and perhaps a link to the company’s website. Try to stick to 3-7 dot points describing each role, depending on how long you were there for and relevance to the role you’re applying for.
Ideally, you will have described what technologies and modeling techniques were used, quantified the size of the data sets and the impact your work has had on the business (or your clients).
As always, feel free to share this with your network and reach out to me if you’ve gone through parts 1 and 2 and updated your resume accordingly. I would love to see a before and after version of your CV! You can contact me on 0430 327 094 or firstname.lastname@example.org