When most data science jobs seek a Ph.D. and several years of experience, it is naturally difficult for fresh data science talent to get their first job. In the scenario, what should fresh talent do? Here are a few tips you can use to get a data science job fast.

Have a portfolio to show off

Recruiters don’t know much about data science. Naturally, they find it difficult to decide a good fit among talent. A few projects in your portfolio will do good. It would help to have links that recruiters can click to view your projects. Most data science projects have an interactive element too. Interactions simplify projects and make it easier for non-technical people to understand analysis.

You can use the following tools to publish projects.

  1. Rpubs
  2. Shiny
  3. Nbviewer
  4. Tableau public

Advance in core data science skills

Python and SQL are core data science skills. Typically, you will need to learn Pandas, Numpy, and Sci-kit learn. These are rudimentary practical skills, which are used directly used on the job. Knowledge and application of these skills should be at your fingertips. It is recommended that you practice these skills as much as these skills become the second nature of your personality.

During interviews, these skills are assessed first. You could encounter programming –based questions like finding “the biggest value in an array”, or find the number of digits in an array, and similar question. Using programming platforms like Codechef, Leetcode, etc are useful to build a strong foundation for core skills.

Find your niche

Data science is broad. Finding which part of data science job you enjoy the most and comes easily to you will set you up for good job opportunities in data science. It would also make it easier for you to zero in roles that fit you perfectly. Essentially, you will need to choose one technical and another non-technical niche.

Following are common technical niches:

  1. R
  2. Deep learning /Tensor Flow
  3. Natural Language Processing
  4. Computer vision
  5. Business intelligence/ analytics

Similarly, non-technical niches include industry and business functions

  1. Finance
  2. Sports
  3. Manufacturing
  4. Retail

The idea is to become an expert in one tool or process other than Python and SQL. Over the next few years, there will be less demand for generalist roles and more demand for niche experts. Companies will seek talent with expertise in tools. The likelihood of getting a job when you are an expert in a niche is greater than when you’re a generalist.

Get a certification

Your projects are definitely the best source for recruiters to gauge your potential for a data science role, but a certification improves it immensely. As a fresh talent, without industry experience, a globally-recognized data science certification will put you forth, making recruiters know that you possess imperative knowledge to work in data science. Certifications are available for all levels of experience, commensurate with roles and responsibilities of data science professionals.

Some popular entry-level data science certifications are:

  1. Big Data Analyst Certification
  2. Cloudera Certified Professional
  3. Microsoft’s Certified Systems Engineer: Data Management & Analytics
  4. SAS Certified Data Scientist

Use advanced job search options

Many job portals including Indeed offer advanced job searches. While looking for data science jobs exclude posts that have a Ph.D. as a requirement and roles that seek a lot of experience. This will help you narrow your choices to select a few jobs. These are the jobs that you have the maximum likelihood of getting.

Additionally, you should apply to jobs that are not older than 3-4 days. As per a report, a recruiter receives the first application within 200 seconds. So for old job posts, your resume is unlikely to viewed by the recruiter. So the best way to increase your chances that a recruiter views your application is sending applications for latest jobs.

Build your LinkedIn Profile

Update your LinkedIn profile with your projects and add a summary of your skills. Many people ignore the skills section on LinkedIn, instead use this space to add your specific skills. This will allow LinkedIn to send you relevant job recommendations.

Additionally, LinkedIn may not be a place to look for a data science job, but building connections with people in the data science industry is a good approach to find job opportunities. Don’t apply to all data science jobs, follow the approach mentioned above to pick out opportunities that have greater chances to fit you. One of the ways is to reach out to people who are hiring data scientist, which is visible next to the name of people. These people are open to job seekers approaching them.

Other things that you can try to become more impressive and attract the attention of recruiters are:

–  Creating YouTube Tutorials in your niche
–  Start a data science meetup or club
–  Write pieces on medium
–  Participate in data science hackathons
–  Create a Twitter account and interact with people you respect

Overall, focus on building your skills and presenting to recruiters in an impressive way. This way you will get a job sooner than you think.