Tips for hiring data scientists
Congratulations! You are selected for the data scientist position – this is the expectation of every data science aspirant who comes out of an interview. At the other end, the interviewer’s task has just begun – assessing each candidate, shortlisting a few and finally arriving at the ‘right’ one. At times, this process might be confusing and hectic. Here’s a list of things that should be looked for in an applicant and might help the interviewer in selecting that right one:
- Programming/Software knowledge – A must for any aspirant, these include programming languages (Python, R, etc.), big data frameworks (Spark, Hadoop, etc.), algorithm design and more. In this world of digital technology, candidates can share their relevant work and projects in platforms like GitHub, LinkedIn to help recruiters know their potential.
- Statistics/Machine learning skills – How can one test these skills? Kaggle to the rescue. Algorithm and statistical knowledge are the core of data science. A Kaggle rank or level says more than anything about these for an individual. His research work in the field of mathematics also tells the quality/the depth of his knowledge.
- A little experience (experience of working with the data) – As Julius Caesar says, “Experience is the teacher of all things”. For any applicant, a little experience of working in the field of Data science/ML makes him stand out among others. Even for a newbie, his internships make him unique.
A person who has different projects and problems solved under his name is more qualified than those who have got several certifications. Above all, the most important thing is a good positive attitude and the hunger to explore, to learn more. A candidate with these qualities will definitely make the hiring process a cake walk. With such members, one can definitely build a strong data scientists’ team.
By: Nagaraj S Murthy