Journey of a Data Scientist at Deloitte Using Analytics: Overcoming Challenges and Promoting Innovation

avcontentteam 18 Apr, 2023 • 7 min read


Are you aware of the challenges that come with a career in Data Science? Meet Anshuman Kumar, a skilled Data Scientist at Deloitte, who has faced and conquered numerous obstacles in his journey. He mitigated from business analytics towards success and became a Data Scientist. Anshuman has developed expertise in the field of data analytics and machine learning, proving that with dedication and perseverance, any challenge can be overcome.

Are you ready to be inspired by Anshuman’s story? Learn how he navigated his way to becoming a leading professional in the industry.

Anshuman Kumar | Data Scientist | Deloitte

Anshuman Kumar, a successful Data Scientist at Deloitte, is a testament to the transformative power of technology in today’s world. With his expertise in data analytics and machine learning, Anshuman has helped clients harness the power of technology to solve complex business problems and drive growth. His success story is a testament to the limitless possibilities that technology can unlock, and the crucial role it plays in shaping the future of industries worldwide.

What will You Learn?

In this article you will get to know the following things:

  • Gain an understanding of the challenges and obstacles that can arise in your data science career, and learn strategies for overcoming them.
  • Develop an appreciation for the importance of data analytics and machine learning in today’s business landscape, and understand how professionals like Anshuman use these tools to drive growth and innovation.
  • Learn about the key skills and competencies that are required to succeed as a Data Scientist, including technical expertise, problem-solving ability, and effective communication.
  • Understand the role of perseverance and determination that helps in achieving professional success, and learn strategies for staying motivated and focused in the face of challenges and setbacks. Especially, while working with Deloitte.
  • Explore the potential career paths and opportunities available in the field of data science, and gain insights into the education, training, and experience required to succeed in this exciting and dynamic field.

Journey from a Business Analyst to Data Scientist

AV: Hello, Welcome to Analytics Vidhya! How are you? Could  you please introduce yourself? And shed some light on your educational and professional background.

Mr Anshuman: Hello! Thank you so much for having me. I am good. My name is Anshuman Kumar, currently, I am a Senior Data Scientist at Deloitte.

Business Analytics at Deloitte

As for my professional journey, after completing my MBA in Business Analytics from Symbiosis (SCMHRD), I primarily work in the technology domain and look into marketing use cases like Customer segmentation, customer acquisition, journey analytics, etc. Most of my work involves a lot of NLP implementation alongside machine learning currently at Deloitte.

AV: That’s great! As you have switched your career from Business Analyst to Data Scientist. Can you tell us about your journey as in what initially sparked your interest and how you began working in this industry?

Mr Anshuman: I started off as a Business analyst, where I got my 1st taste of analytics. An important thinking that I learned from that was, the abundance of data will only grow in this digital age that we are in. Data science is one stream that will  help one leverage this growing data repository to help predict the future. Furthermore , it’s a field that perfectly blends automation and prediction, these 2 components that will always be the need of the hour.

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AV: Wow! Since you have MBA in Business Analytics, How has it influenced your approach to Data Science? What unique insights or perspectives has it given it to you in your professional journey?

Business Analytics word cloud
Mr Anshuman: An MBA in Business Analytics, helps me maintain a business vision at all times. What I mean is, most of the time as data scientists we get caught up in the complexity and beauty of the math behind the algorithm and end up using complex techniques to produce an outcome that may not really be appreciated or consumed by the masses. That’s where we lose the business vision and turn into an enthusiast. While the whole idea was to preserve business sense and keep things as simple and easy to consume as possible. So in a nutshell my MBA helped me preserve the business vision in my approach, and also maintain a holistic view of the business problem.

AV: That’s thrilling! So, based on your experience at Deloitte. What all skills or qualities you think are necessary for a successful Data Scientist?How have you developed these over the course of your career?

Mr Anshuman: The most important qualities for being a successful data scientist would be being inquisitive, being a good storyteller and most importantly being a great problem solver. The way I developed these skills was through involving  myself in different types of projects or use cases. This helped structure my thought process and approach. I also subscribed to various blogs like Medium and AI discussion forums to help keep myself updated on  the latest developments.

AV: How do you balance the technical aspects of data science with the business needs and goals of your organization? What strategies have you found most effective in bridging this gap?

Mr Anshuman: The only way to do that is by effective communication, and here is where the art of simplifying things comes in handy. The only way to do that is by not being too technical in explaining your ideas and instead showing business value in what you do and what it is capable of delivering. And keeping the business in the loop all through the journey.

AV: How did your experience at Meta prepare you for your current role at Deloitte? How has your approach towards  data science evolved over time?

Mr Anshuman: The best part of working at Meta was the length and breadth of data that one is exposed to, it gives you a perfect taste of how working real world data and problems look like. Frequently with Kaggle competitions and practice projects the data is in such an ideal state, it needs less to no amount of cleansing, while the real world is far from that. Meta helped me fine tune my data cleansing skills and also gave me an overall experience of a full scale data science project implementation.

AV: Can you describe a recent project or initiative you’ve worked on that has utilized cutting-edge Data Science techniques or technologies? Additionally, How does it differ from your previous experiences?

Mr Anshuman: Recently I worked on a real-time speech classifier, in which we used spectrography to understand and train our voice data. This by far is one of the most advanced implementations of NLP I’ve been involved in. Yes it does differ a bit , since most of the use cases are classification or regression based, hence getting an opportunity to work on such use cases is a  bit rare. The thing that separated this experience the most was the use of transfer learning techniques.

AV: Can you describe when you had to work with messy or incomplete data and how you could still extract meaningful insights?

EDA | Business Analytics

Mr Anshuman: By using a lot of data cleaning and feature engineering techniques like Boxcox plots, outlier detections. Primarily using basic statistics to transform the data to preserve the meaning and make the data usable and ready for analysis.

Points of Reflection

AV: How do you see emerging technologies like Machine Learning, Artificial Intelligence, and Blockchain shaping the field of Data Science. What new opportunities or challenges do you anticipate as a result?

Mr Anshuman: The emerging technologies will only help democratize the field and open it for everyone. Maybe in the near future it’ll open up the data science field to all the industries. While that does mean more opportunities in terms of an increase in the requirements of data scientists and engineers. It also will bring its own set of challenges, for e.g. it may expand the list of prerequisite skills to land your 1st job as a data scientist.

AV: What are some of the most important lessons you’ve learned over the course of your career? How have these informed your approach to Data Science and problem-solving more broadly while working with Deloitte?

Mr Anshuman: The most important lesson would easily be, whenever you are ideating a data science solution keep the end user in mind. Rather than considering the most fancy algorithm, always go for ease of use and business value over everything. That is why in all my approaches I at first refrain from using something that is unnecessarily too complex.

AV: As a Data Scientist at Deloitte, What are three things you are most proud of? How have they helped you shape as a person?

Mr Anshuman: The 3 things would be :

1. The opportunity to work with some of the smartest people. It is always a new learning experience when I am in a room full of smart people, way smarter than me. It helps me improve my knowledge and forces me to get better as a person everyday.

2. The opportunity to help solve some of the most complex problems. It always gives me a sense of accomplishment. When I am finally able to ideate a solution for something that is highly complex. This helps me remain motivated.

3. An opportunity to contribute back to the community by helping others. The fact that I can contribute back to society by maybe mentoring or helping others. Looking for advice in this line of work keeps me driven and fulfilled.

AV: What advice would you give to someone who is interested in pursuing a career in Data Science? What skills or qualities do you believe are most important for success in this field?

Mr Anshuman: I am a firm believer of the fact, tools and technologies can be taught, but qualities can’t. For all aspiring data scientists,

Please always be ready to learn, stay hungry, keep learning. Always stay inquisitive.

AV:  Thanks for your time! Definitely, this will be helpful for all the aspirants who want to go into Data Sciences or Data Fields. So, Let’s conclude today’s discussion.


The success of Anshuman Kumar is proof of the revolutionary potential of technology. His transformation at Deloitte from a Business Analyst to a highly accomplished Data Scientist is a prime example of the value of commitment, and tenacity, in achieving professional success.

Anshuman has aided customers in using technology to solve challenging business problems and spur growth through his experience. His accomplishment serves as motivation for aspiring data scientists by illuminating the essential abilities and knowledge needed to succeed in this fascinating and fast-paced industry.

Anshuman’s story serves as a reminder that anyone can achieve their career goals. You could have a substantial impact on the sector with the correct attitude, resources, and tools. He is a living example of the revolutionary power of technology and his ability to influence a wide range of businesses in the future.

avcontentteam 18 Apr 2023

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