Aspirants and professional data science today swear by the popular and trending buzzwords. They use their energy in taking up numerous projects and eventually get exhausted. Rather than padding their resumes, aspiring data scientists should work on specific projects that have not been done yet. However, since most of the MOOCs have projects like house pricing prediction or flagging frauds, developers fail to differentiate their capabilities. Besides, deploying machine learning and deep learning techniques are not enough to obtain job offers, one should have the business domain knowledge along with data science techniques for assisting firms in making informed decisions.
To help students adopt best practices, Analytics India Magazine interviews prominent data scientists every week and brings out their story to help aspirants understand the right approach. For this week, we got in touch with Bastin Robin, Chief Data Scientist at CleverInsight, for our weekly column My Journey In Data Science.
Robin’s Interest In Computer Science Began With Designing
While in school, Robin was in love with computer science. However, it was more inclined towards designing than programming. He created a portfolio pertaining to design, which helped him in getting various freelance jobs. Eventually, he turned his passion into a business and started a firm called W3Graphix in 2009 – a design consulting company. Although Robin was earning before even joining the college, he enrolled in an engineering college to get a certificate.
Love And Hate For Programming
Robin pursued computer science engineering, but he wasn’t interested in programming. However, his Head of Department, who had a PhD in data mining, used to push him to learn to code. The HOD used to say that Robin could not become an engineer if he does not learn to code. But, Robin did not agree and believed not everyone is the same; he was confident of having a great career without the programming skills. Irrespective of Robin’s interests, the HOD kept pushing him and explained the importance of programming for being competitive in the tech world.
According to Robin, he was doing well in college and was selected as a Microsoft Student Partner. However, one morning, he decided to heed and for once do what his HOD expects from him. “The cold war between me and HOD lasted for too long. And since he was insisting, I thought about giving it a try, explains Robin. “And it changed everything for me,” he added.
Unlike others, Robin didn’t start with popular languages like C, C++, and Java. He went to the library and picked up the book introduction to programming. The book had lessons that were explained in Python programming. Robin immediately fell in love with the book, and for the next two to three months, he read it like a bible. “That’s the only book I carried to the college and people thought that I had gone mad,” says Robin. “C and C++ are very sensitive to syntax, whereas Python is more of an expressive language. Therefore, anyone who learns Python enjoys it from the very beginning.”
First Data Science Job
While being in graduation, Robin was asked to teach M.tech students due to his Python programming skills by one of the assistant associate professors. Within no time, he was able to convince the class filled with M.tech students the essence of programming, and this made him believe that coding was his cup of tea.
During his final year, one of the students from the M.tech informed Robin about the opening at Gramener. Immediately, Robin applied through its career page and was asked to solve three data science problems. On submitting the solutions, he was called for a face-to-face interview with the CEO and VP of Gramener in Hyderabad. Impressed by his skills, Robin was offered the associate data science job by the management.
While working at Gramener, Robin worked on various use cases to help the firm achieve its business objectives. One of the projects that really made the difference was optimising the logistics with data science practices. “Data science has four pillars: past, present, future, and the action. It is not about the tools rather, data science is to make informed decisions that require business knowledge. Consequently, the fourth pillar is of utmost importance,” believes Robin.
He further went on to say people try to focus on machine learning and deep learning techniques, but data science is about data, not fancy ML and DL. Positive ROI is what matters the most, which can only be achieved by obtaining business domain knowledge.
After being with Gramener for a few months, Robin was motivated enough to start a data science firm that would offer SaaS-based data science platform, where one can drag and drop to visualise. Therefore, he laid down the cornerstone of Hash Research, which immediately got traction from various businesses. Further, he started working on multiple use cases and showcased his capability using platforms like LinkedIn and blogging sites.
Passionate to further enhance the product of Hash Research, Robin along with Kothandaraman Sridharan, founder co-founder of Mphasis, established CleverInsight that acquired Hash Research. “We built a platform called Neuron AI, which was basically an advanced version of the product of Hash Research, litmus,” describes Robin. “Neuron AI is an ecosystem where one can build many use cases on top of it.”
Advice To Data Scientists
Aspirants and professionals of data science mostly focus on projects that are already available on the internet. For instance, people try to refine their resume with projects such as fraud detection model, image classification model, and more. However, Robin says that there is nothing new in it; such projects are all over the place. Instead, he suggests developers should create dummy datasets that can resonate with business problems and then try to ask various questions and solve them accordingly. Going one step further will assist them in demonstrating your capabilities and quickly get their desired jobs. “Interviewers look at how the applicant started from zero to end. The process of doing specific cases will impress any recruiter, thereby increasing the possibility of receiving a job offer,” concludes Robin.