Data Science career is blooming and the demand will only increase! Currently, we are living in a world of Information Technology fueled by Big Data and AI enhancing customer experience and the creation of personalized products with data-driven approaches. "The job of a data scientist has only grown sexier," said Andrew Flowers, an economist at Indeed, based in Austin, Texas, and author of the Indeed report. "Increasing number of employers than ever are looking to hire data scientists."
With such a huge demand around the world, people are focusing on developing their skills regarding the subject but often become chaotic with questions like How to become a data scientist? What skills are required? What educational background you must have? and so forth. In this article, I would like to share my personal experience and the journey to become a data scientist.
Staring at all the job description about the data scientist, we typically notice that many organizations generally ask for a Ph.D. Degree in Statistics or Mathematics with extensive skills in multiple programming languages like R, Python, JAVA, etc. and database expertise. However, for an individual to develop all these skills might take several years of dedication, back-breaking work, and patience. Even after acquiring all these, there is no certainty of getting a relevant job. In contrast to the job description, there are significant numbers of people getting hired as a Data Scientist who are recent graduates. What I believe is the skill that plays an important role in getting a job rather than pursuing a heavy Ph.D. degree. In order to develop the right amount of skills and get familiar with the tools and technologies as this field is growing rapidly and evolving overnight, one needs to be flexible in learning new things and put extra efforts to practice.
Background: Sharing my personal experience in this journey, to put it simply, it has never been easy. Even today, No Data Scientist ever have said they have enough skills and tools to apply in their projects. It totally depends on what kind of problem you are dealing with and what approaches you follow to solve that can create an impact on revenues and sales in the company you are working for. Talking about my educational background, I only have a Bachelor’s degree in Information Management, a blend of Information Technology and core management principles. During the halfway completion of my program, I had an interest in Networking and Data Communication and this was the time when I decided to gain practical experience with networking devices which included configurations and troubleshooting. I started working as a Networking professional in a prominent Internet Service Provider with a customer volume of around 200 thousand.
Gradually, I had a transition in my career which primarily originated after my promotion to a senior level generating dashboards and reports indicating the performance of internal network architecture and the services provided to the customers. The massive data generated by customer service, in particular, problems reported by the internet users, the actual problem they have faced and the solutions suggested in order to avoid any disruption in the service was really conspicuous. The patterns that I noticed while exploring the data and the curiosity to identify the root cause shifted me towards learning programming and tools to describe and make inferences from the data.
To have a solid background on programming techniques and database systems, I started learning the fundamental principles, algorithms and database schemas which eventually led me towards mastering data manipulation and performing analytics to extract meaningful patterns and insights from the data. However, JAVA had its own limitations which propelled me to assimilate Python and its libraries that are really useful for performing data preprocessing (Cleaning, Imputation, and Transformation), engineering, visualizing to detect patterns and trends from the data and applying different machine learning algorithms to best fit and predict the result. For instance, with my knowledge in this topic, I was able to identify patterns of real problems faced by the customers, segment them according to the nature of their problem, predict the appropriate solutions and recognize the sentiments of the customer which were submitted as a complaint or feedback. During the time of my research and learning different programming languages, assistance and mentorship of Mr. Dixanta Bahadur Shrestha of Creators Institute of Business & Technology (CIBT) were imperative and I’m very thankful to where I stand today.
In overall, I would like to say that anyone can become a data scientist no matter what your educational background is or even if you have not done programming yet, the only things you required is dedication towards your learning path, passionate about the data and business value which can be generated and lastly patience unless you achieve what you strive for. Everything is difficult before it’s easy and possible only if you start!