Want to know how to make an impressive data scientist resume. Creating an impressive data scientist resume is not just about using killer graphics, but emphasizing the high points effectively – work experience, MOOCs, learning background, real life projects you deal with and your technical skills, especially statistics because that will count the most.
With the data scientist field picking up steam, and jobs being in high demand, it is important you set yourself apart from the competition by playing on your strengths. According to our research, most recruiters who are hiring data scientists, look out for these key points — past internships and work experience, participating in hackathons, ease with programming languages R and Python, also the resume should be peppered with Machine Learning terms. Don’t forget to add behavioural attributes such as team player, problem solving skills, thrives in small teams, innate curiosity and a sharp business acumen.
Here’s our guideline on how to create the best data scientist resume
Here are tips on building a solid data scientist portfolio that will definitely wow the recruiter’s:
Show off that advanced degree: While top hiring companies prefer doctoral candidates, a master’s degree in computer science works. Emphasize your educational background and your academic credentials clearly and lay down your expertise in applied statistics and mathematics as well.
Ease with statistical/data analysis tools: This is a major prerequisite as most recruiters want a hands on experience with data analysis tools. Write down your experience with R and SAS or any other data analysis tool you have worked with. Remember, hiring managers aren’t just looking for a candidate with purely academic background, they need someone with who knows how to use data analysis tools.
Experience with huge volumes of data: Your job is to work in big data and the sophisticated skills of data scientist comes into play when dealing with high volumes of velocity of data. Make sure you jot down your experience with Big Data projects and the scalable models you built for businesses through machine learning, predictive modelling and data mining techniques.
Understanding of business domain: Stellar academic credentials aside, most organizations also want a business savvy person who can understand the specific industry and what business problems your company is trying to tackle. Also, the role of the data scientist here would be to identify how the business can better leverage their data for maximum gains.
Communication and soft skills: Business acumen is extremely important because data science is all about problem solving. Most companies are not looking for a data nerd, they are looking for a high acumen member who can be a part of their global team. Your job as a data scientist would also entail to communicate the findings from complex models and analysis in a cogent manner to people from a non-technical background. Brush up those communications skills and sail through the job interview.
While data science is the hottest field, there is no set job description as most organizations are still learning how to deal with reams of data. But if you have experience, set yourself apart from the crowd by crowning your accomplishments – real life datasets and demonstrate your ease with next-gen tools. With these tips, you can create a stellar data scientist resume.