“Two things remain irretrievable: time and first impression.”
No wonder, a Curriculum Vitae was a prerequisite for landing a job role in any industry. But, in today’s competitive times, we’re pushed by the demand for providing more than just the bare minimum. A filthy rich portfolio leveraged with credible data science certification is a critical ingredient in getting closer to your dream data science professional job role.
With humungous data surging with every passing day, it has made itself an integral part of our existence. Neither any business nor personal routine is free from data. If your portfolio looks too generic; or lacks elaboration and interesting projects, it can get hard for you to fulfil your data science dream.
The days are long gone when recruiters will be satisfied with the basic qualifications. It all comes down to the expertise and pool of skillset that you’ve earned during the courses or certification for the role. Projects and internships (paid or voluntary) add much-needed value to your data science portfolio. Not everything must be looked at from a monetary point of view. Stay proactive and showcase the best of the data science skills that you possess. Let us understand the key insights for developing the best data science portfolio.
A data science portfolio is a collection of the best work and demonstrates your skills as a data scientist. A data science portfolio features a combination of your code and documentation and some writing samples showing your ability to communicate effectively about data.
An aspiring data science professional values and understands the worth of the time invested in building a high-quality data science portfolio. Developing your portfolio based on internal motivation forms the right base, thereby leveraging a genuine feel to it. This also pushes you to get your data science certification and as a certified professional to put in your best for the offered role. It is critical for any data science aspirant to invest their time in building a quality portfolio as;
Recruiters looking for experienced data scientists expect them to be able to manage large amounts of data and analyze and process the same. A good portfolio is definitely the cherry on the cake that grasps employers’ attention. They are keen on deploying professionals who can analyze data using varied techniques and tools. Core ability to communicate findings clearly and concisely is a quality that takes you a long way ahead in your data science career. Whether you’re a newly qualified data analyst or a seasoned data science professional, you’ll need a portfolio that pops. Why wait? Build a strong portfolio today!