It was March of 2006. I was nervously waiting outside the placement cell for my turn while memorizing some concepts from my favorite Philip Kotler text book on Marketing. During my 2 years of MBA course, I picked up a penchant for understanding the dynamics of a business and its customer. My internship with a software firm was also based on customer account mining and my research paper was on the then onslaught of global brands on local brands. I was hoping to crack a research firm or a global company with niche market. And so I started my corporate career with a US based supply chain software company, in a marketing operations role. A significant part of my job was to look into loads of leads and customer data and drive marketing initiatives on a global scale based on dashboard reports I used to generate from the company’s CRM Salesforce.com. That was around the same time Salesforce.com was stepping up its game from just a CRM provider to an on-demand application provider, and a couple of its early apps enabling better customer data capture, pipeline management, forecasting etc got rolled out to my teams. I really loved my job. On the other side, I was engaging with my school buds on Orkut, some of whom I last saw was over a decade ago. I was seeing beard and mustaches on the faces I only recalled from 4th grade, the girl I last remembered in two oiled plaits was now some fashion diva. I wanted to see more! If only there was some way Orkut could show me suggestions! Fast forward 13 years, I realize I should have treated y=mx+b with more love back in school. Here I sit writing an article as part of my Data Science course, not knowing how to limit this to a few hundred words given that every day of our lives is full of probabilities.

I have a thing for art. I am quite visual in that a good print ad will buy me. I have won all of the drawing & painting, craft, handwriting, rangoli, ikebana competitions in school. I went to embroidery and knitting classes. I went to dance school. I follow fashion. I would never give someone something that wouldn’t please me first, including the PowerPoint presentations at work. Crisp, minimalist but 100% insights. Or not. I’d give it 99.99966% today. Starting from marketing operations, I have assumed multiple roles in business strategy, research, master data management, data quality and program management. In my quest for data analysis, I was also freelancing online. All along, I have never had to know what the engineer was doing in order to power my team’s work. I only knew what to ask of him. I thought coders were magicians, and would attribute some of my successes to their support. It was on my agenda to learn the back end some day. What was the probability that my hobby would take over? I became an entrepreneur in 2015 when I ventured into a dance education startup aiming to grow the American street dance community in this country. I had trained in the authentic dance styles from the 60’s & 70’s American hiphop revolution, and dreamt of introducing it as a formal education here. It took a long time before my data correctly started projecting the market isn’t ready for the product, so while the idea was shelved, I got involved in assisting with my family run businesses, mostly looking into the resort business managed by husband. I feel a lag. I have been thinking what is it that I might have missed evaluating, in making a product that was indeed exciting for my prospects, a worthwhile purchase? Is there more to the data that the resort is churning out? Additionally, my online freelancing profile got removed and the reason cited – you’ve been inactive for a while and your skills are too common! Turns out that the lag is real.

I went on a week-long pursuit of what’s next. Search for top skills of the year / best career path / highest ranked jobs, everything leads to Data Science. Why, even my good old job roles now sport “Python knowledge nice to have” in the JDs. That’s it, the near long term has suddenly become clear to me, I quickly
signed up for courses online and offline and started enrolling for webinars etc., and set my foot on the path to starting a consulting firm in the Data Science domain. I chose ExcelR Solutions, a top-rated institute for a certification program in Data Science. The thriving businesses of today are the ones that have taken their data seriously AND acting upon the insights obtained. Data Science is popularly being associated with the Industrial Revolution 4.0 with big data being the new electricity. Even as robots and automation have been around for many years, in the context of what analytics can do, only the surface has been scratched. It is exciting to know that most things that drive our lives today are driven by this fascinating subject, and as a Data Scientist how big a scope one has, to significantly impact individuals and businesses. My college fascination now has a complete make over!

In the first seminar I attended on Data Science, the speaker made a statement inspired by a **popular saying that sounded something like, “A data scientist does not know more statistics than a statistician, or more programming than a programmer, but can beautifully fuse both together for some amazing outputs that neither of them can”. That got my heart. For the first time in my life, I actually began to appreciate the annoying things like spam emails, dynamic pricing of flight tickets, website/social media ads, online feedback forms, credit card calls etc. Of course we all love to see the viewer stats on our LinkedIn profile, posts of our interest from around the world on Instagram, movie recommendations of our taste on Netflix, chatting (non)sense with Voice Assistants on our smartphones, product recommendations on Amazon and a plethora of custom features as if the whole world is seeking out for you. Ego has never been so satisfied. From the day I went online researching on Data Science to this date, my facebook feed has at least 5 ads per browsing session showing me institutes offering the courses, webinars in the next week, related articles etc. What goes into all these? A bunch of algorithms from high school algebra that have now started to make sense. Machine Learning demo is not even a thing that you need to go on YouTube looking for – it is exactly what your personalized feeds are made of! Want to know whether you will make it safely to your next travel destination by flight? Want to know whether you’re likely to fulfill your last year’s resolutions this year? or next? or the year after? Or in how many years will you actually fulfill them or not at all! Probability distributions have the answer. Just grab the right data. Probability distributions are also foundation to model outputs that fuel critical business decisions. The central limit theorem is certainly one of the most beautiful models which, apart from what it does to data with largest of variations, inspires us to hope that even from the most erratic situations in life, one can establish harmony if one learns to address the smaller issues. While all this may not promise to tell you a definitive outcome, sure will you have better information to ‘expect’ a certain outcome. Remember it is called ‘probability’. The data visualization options are what excite me the most – being able to look at the data most imaginatively and present it most creatively.

While we are all game for what’s coming to us unsought for, we may also give an alternative thought as to whether this is limiting our chances to know what more is out there? What it means is whether in all the tailor made information being flooded into our daily feeds on multiple platforms, are we restricted to a certain type of information only? Well it is a consolation to know that Machine Learning is only a machine – learning from what we feed it with. It is still the human’s job to program the machine or induce what it must learn. In the race of man vs machine, we can safely assume that as of today, a machine can wreck your life only in Transformers.

My first ever casino experience at Caesar’s in Atlantic City in 2010 got me raving about how much money the casino was making. I didn’t see any gambler make as much, but the dealers were surely counting all the time. I made $2 from a slot machine after giving $20 and I did not even attempt roulette, wheel of fortune or the card tables. After many visits to casinos during my various travels, I observed that some gamblers were ‘studying’ the patterns. Is it possible to win against the best odds these machines are designed to throw at you, by following a certain pattern? Turns out it is, and I recently figured at a roulette table. You could plan your bet just by intuitively following a pattern. This is some kind of probabilities at play! It is interesting to know how the casino businesses use analytics to ensure they make money while also ensuring the gamblers don’t have too many unfortunate visits. I am curious to know whether my next travel as a data scientist would be more rewarding!

**A tweet by Data Scientist Josh Wills “Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.” in 2012 has been made famous with different versions since.