Meet Rishabh Dhingra, an accomplished professional excelling in Analytics and Data Science at Google. Rishabh possesses extensive expertise and a passion for utilizing data effectively. He drives innovation through advanced technologies, extracting valuable insights and revolutionizing data-driven decision-making. Rishabh’s journey at Google has been remarkable, transforming the Analytics and Data Science domain. Let’s explore his achievements and contributions that have propelled Google’s success to new heights.
Mr. Rishabh: I started my career as a BI Consultant with Thorogood Associates in 2011 and have worked in Data Space since then. So learning languages like SQL, Python, data modeling, presentation skills, and tools like Tableau are the initial required steps in the journey. And then, some people start by going deep into math and theory and doing some projects. But I feel doing it and then understanding the concepts as I apply work the best. Some key steps that helped me:
Mr. Rishabh: As a successful data scientist, I believe that the most important skills for aspiring data scientists to have are:
I developed these skills by taking courses, working on personal projects, networking with other data scientists, and learning from their experiences.
Mr. Rishabh: I think these are mistakes the data scientists should avoid:
Mr. Rishabh: My suggestion is to take two types of projects – one that aligns with your business that you work closely with – this could be taking on stretch projects within your job and trying to add value to the business and would also help you learn on the job and make an impact. And the second type of project would be your passion project. For example – if you are into sports, pick a dataset related to it, build your hypothesis, and do a project on it.
Mr. Rishabh: I really enjoyed my time at Home Depot Canada and was fortunate to be exposed to various data science challenges. One of the learning experiences that is very underrated, in my opinion, is defining the business problem and success metrics of data science projects, and getting alignment with all the stakeholders is very critical for the project’s success. This would guide everyone before jumping into solutions to the problem and building things, analyzing the business problem, and defining the success.
Mr. Rishabh: Youtube – I go to Youtube to learn anything and find answers to all my “How To” questions. It has so much content and info available for us to learn new skills – ML/AI or how to cook ‘Biryani’ – it’s all available on Youtube.
Mr. Rishabh: I engage myself in a lot of things outside work – listening to podcasts and running my podcast ‘Inspired’, playing sports, especially cricket, being an instructor on data analytics and data science, mentoring new immigrants in Canada, reading books, running my side hustle business of home decor. Balancing all this with professional life sometimes becomes difficult, but that makes life interesting and keeps me going.
Mr. Rishabh: As a leader, you need to have both a long-term vision and short-term wins that would help the business. You need to be very clear and communicate the long-term vision of the analytics journey to the stakeholders and your team so everyone is clear on how the future will look and what steps we need to accomplish to reach it. But you need to also seize the moments in the short run where you can impact the business using analytics. However, your short-term decisions must align with your long-term vision. I suggest identifying and going for quick wins to make an impact that aligns with the long-term vision.
Mr. Rishabh: The field of data science is constantly changing, with new technologies and techniques emerging all the time. Data scientists must constantly learn and upskill to stay ahead of the curve. Some ways I keep myself updated on the latest developments in the industry are:
Mr. Rishabh: I think the future will be AI; you will see AI embedded in every aspect of our life. So, there will be a lot of demand for AI developers/engineers. New machine learning and AI techniques will be developed to solve real-world problems and make us more productive. Like we see how Generative AI is making us more productive these days. You must have seen the announcements that Google made at I/O 2023 event on the great AI features coming to Google products and how they will make us more productive. I also think open-source data science tools and libraries will continuously grow. My goals in this field would be to find real-world problems where we can apply the new ML/AI techniques and educate others about my learnings, and I would ideally want to get into Product Management in ML/AI.
Mr. Rishabh: Below are the things I would suggest for companies looking to implement a BI and Analytics solution like Tableau:
Books
Courses
Applied Machine Learning – Beginner to Professional by Analytics Vidhya
Podcasts
Newsletters
Podcasts
Books
Website
Books
Podcast
In conclusion, Rishabh Dhingra is a true exemplar in the Analytics and Data Science domain, leaving an indelible mark on Google’s groundbreaking work. His exceptional skills, unwavering dedication, and remarkable ability to provide insightful guidance make him a valuable resource for those entering or transitioning into the data science industry. Rishabh’s commitment to sharing knowledge and empowering freshers with invaluable insights in analytics and data science ensures that the next generation of data scientists will have the tools and inspiration to succeed. As Rishabh Dhingra continues to revolutionize the field, his impact on both Google and the broader data science community is a testament to the boundless possibilities ahead in this dynamic and ever-evolving industry.
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