Get a Job in Data Science: 6 Key Factors for Getting Hired
Data science has proven to be a remarkable field throughout the years, leading the 2019 list of 50 best job for the fourth year in a row as ranked by Glassdoor. These statistics confirm one thing; there is no better place to work in than in data science.
So, what is the sure-fire way for a fresh graduate or junior data analyst to get a high-paying job in data science? Here’s what to do to get employed:
Identify the Role That You Want to Pursue
Data science encompasses several different jobs. Yet, even the same job title may have varying responsibilities from industry to industry. A data scientist in one organization may work either in algorithms, analytics, or interpretation teams. In another, the roles may not be as well defined, and the data scientist will need to wear all three hats. Find out if there is something you are leaning towards and make it the focus area.
Take Courses in Machine Learning, Python, Hadoop, and SQL
To get the attention of relevant employers, one must possess the skills they are generally looking for. So, immersing oneself in acquiring relevant data science skills by taking online courses is the best next step or one that a person can do while still applying for a job. Top demanded technical skills for data scientists include programming (preferable R and Python), machine learning, statistics, data visualization, Hadoop, SQL, and Spark.
Build Networks and Apply Persistently
Just like with any other job applications, there is bound to be disappointments and rejection. Hiring managers may have a lot of applications to review daily, so getting noticed is not easy at all. Find and get in contact with prospective employers on LinkedIn and data science forums. Build networks that can help you push the job application.
Before the Interview, Do In-Depth Research on the Employer
Perhaps the most important tip for cracking an interview is getting to know how the company operates. Learn its business model, their competitors, the challenges they are currently facing, and even the company culture. This knowledge will show the employer that a candidate has gone above and beyond to learn about their company which means they are genuinely interested in the position.
Prepare for the Job Interview Questions
Go through examples of possible interview questions and practice answering them. It will only do you good as prior practice boosts confidence and shows how well-prepared you are. It doesn’t hurt to have an elevator pitch ready too.
Make a Follow-Up Promptly
After a job interview, it’s a good practice to send a thank you email or letter to follow up within a day. This is not only beneficial to the candidate but also raises an opportunity to reinforce their unique strengths and suitability for the position while also answering any concerns arising from the interview. Check in again after a few weeks of no response but don’t be pushy.
With these tips, getting a job in data science is not that hard. Anyone who has gone through the process of applying for a job multiple times knows that early preparation is key. Know the type of interview that will be conducted and prepare accordingly. Don’t forget to update the resume. All the best!