Apoorva’s Journey of Challenges and Growth as a Data Scientist

Introduction

Welcome to our success story interview series, where we bring you inspiring stories from successful data scientists who have made a name for themselves in the field of data science. In this interview, we will be talking to Apoorva Kakde, a data scientist who has made significant contributions to the field and has carved a niche for themselves.

In this interview, data scientist Apporva shares her career journey, challenges faced, and skills necessary to succeed in data science. She emphasizes the importance of problem-solving skills, as they are necessary for defining problem statements and understanding requirements. She also discusses a particularly impactful project where an automated test plan was created, highlighting the importance of communication and presentation skills.

We’ll explore her journey, challenges, and how they overcame them to succeed. Through this interview, we hope to inspire and motivate aspiring data scientists to pursue their dreams and achieve their goals.

Interview Excerpts with Apoorva

AV: Can you share some of the biggest challenges you faced during your career as a data scientist and how you overcame them?

Apporva: The most challenging part for me was the transition. From developer to solution designer to senior engineer, the thought process required to provide data science solutions is entirely different. Simply put, using the reference from the book “Practical Machine Learning with Python” by Dipanjan Sarkar and co-authors, how traditional programming and machine learning look like.

AV: How did you first become interested in data science? What steps did you take to start your career in this field?

Apporva: In late 2020, I wanted to transition to another field as I felt my growth was stagnant, being a solution designer/lead for 3 years. I started exploring the recent trends and extracted my top 3 options of data science, cloud, and data engineer/analyst. Confused, I spoke to people in the field over LinkedIn and some close networks to understand what would be best for me. Then I decided to give data science a chance for transition. I worked with Intellipaat for 7-8 months and understood what and how data science works. Now it was time to gain some practical knowledge.

Soon, I got an opportunity at TCS to work on a computer vision project, which was my first experience in data science. I made many blunders, but the best lessons are learned through mistakes. The only mantra to learn data science is “Make many mistakes.”

AV: What are the key skills and qualities should aspiring data scientists focus on developing to succeed in this field?

Apoorva: The most crucial skill needed here is problem-defining and solving skills. Technical skills can be learned on the go once the basics are done. Understanding the requirement and defining the problem statement is the most challenging part for the mid-senior/senior professionals, as the entire team relies on you. The funniest part is that when you start working, you will realize that the problem defined is not even a problem. Aspiring data scientists should work on this as it is not taught anywhere; it comes with practice and experience. With experience, I mean not in years, but with no projects done.

AV: Can you tell us about a particularly impactful project you worked on as a data scientist and what you learned from the experience?

Apporva: The most challenging project we had was automated test plan creation. In this project, we developed a process to take input data, create and update the database and include an ML model. The most challenging part of the project was to know what was needed and gather the data. Since a manual process was being automated, it was the real challenge. Apart from technical, I learned some crucial communication and presentation skills. It was a great experience leading this team.

24 Ultimate Data Science (Machine Learning) Projects To Boost Your Knowledge and Skills (& can be accessed freely)

AV: Can you share some of your favorite hobbies or interests outside of work? How they have impacted your career or personal growth?

Apporva: 2020 gave me considerable time to reflect and work on myself. I wanted my better version for a long time, but it remained a thought. Finally, when I got a chance, I joined a book club, started reading considerable books on self-help ( now I have a mini library), and started my own blog and youtube channel with the name solvingyourlife.

How did it help in my career?

I firmly believe that life changes when you are willing to change and think differently, thus changing your patterns. The approach towards life changes. For example, when I started data science, I felt like quitting as I could not understand anything. While going through some self-help stuff, this statement got me,” If you are not born with talent, learn it. If you do not have any experience, get it. Consistency is the key.”

This got me going, and things started to fall into place. Thanks to my trainer Shivam who gave excellent sessions. Slight philosophy here, but when you are ready, the universe will place you with opportunity, which in my case, came up with a computer vision project.

I also started practicing mandalas, which brought patience and calmness to me. Now I have started gifting mandala frames with self-help-quotes to my close friends and relatives. Finally, I have attained a baseline to ditch Netflix at 9 pm and practice mandala/read books which is growth.

Although I am currently inactive on solvingyourlife for a long time during and after pregnancy, I look forward to restarting it. Being on childcare leave with my twins, I still read whenever I get time, thus improving my thoughts and skills daily.

AV: How do you stay current with the latest data science and technology developments? What resources do you recommend for others looking to do the same?

Apporva: I follow a few people and AI startup pages and have joined some groups on social media. I do join related meetups, and it keeps me posted.

For Leaders on LinkedIn: Andriy Burkov, Pau Laberto Bajo, Mohammad Arshad

For Research Papers: Papers with code

For blogs: TowardsDataScience, KDNuggets, AnalyticsVidhya

AV: Can you share an instance where you applied skills learned from your hobby in a project at TCS?

Apporva: I would like to share some learnings I have applied from some of the books I have read.

• Atomic Habits: Building up habits by introducing processes in between tasks. For example, whenever a task is assigned, think through it and write how it will be executed(step-wise). This brought clarity of thought to proceed instead of being stuck and confused.
• Attitude is Everything: Get more experiences. I mentor/ provide consultation to other teams with similar technologies.
• The subtle art of not giving a F*ck: Pay attention to the things that matter to you. Take a stand for what matters to you. It helps me disconnect and avoid unnecessary conflicts whenever unpleasant things are around.
• What to say when you talk to yourself: This plays a crucial role when things are unplanned. Everyone makes mistakes, but finding solutions is more important than going into negative loops, and it is more about being kind to yourself and increasing self-esteem.
• Compound Effect: Never break the cycle continuously for two days in a row.

This helps me to keep everything on track for the team.

AV: What aspects of your job as a Senior Engineer, Data Science at Tata Consultancy Services are most enjoyable and fulfilling?

Apoorva: My most enjoyable tasks are requirement understanding, Architecture/design, and team mentoring. I always wake up at 5 am for these requirements and design parts and start working with pen, paper/whiteboard. Once I get the clarity, I come to the digital part. Though we are in this ultra-digital age, I believe the best ideas come on paper. Since it is mostly single-handedly done by me, it is fun to do this deep work, and when it is done and submitted for further discussions, that feeling is priceless. Of course, versions are updated after meetings.

I like mentoring my team, technically and personally (since I am in the self-help area).

AV: What particular skill or area of expertise do you bring to your role as a Senior Engineer in Data Science at TCS, and how do you apply it to your work?

Apporva: Problem-solving is my core area. Asking the right questions and getting the correct input is the skill that works for me.

AV: Have you ever implemented data science in your personal life?

Apporva: I created a small code for predicting the baby’s schedule(it is in progress). It all started with my confusion about meal timings. We were unable to recollect which baby had a meal at what time. So we started maintaining a small diary to write meal timings. Slowly it included sleep timings, poop timing, etc. Being a data scientist, I used to refer the past data and predict the schedule in the diary rounding off the things that were not as expected. I used to take the difference manually and recalculate it again for the next few days. I have considerable data from 7 months now, so it is easier to predict the schedule. Though every day is different, 50% of it works.

AV: What advice would you give students pursuing a Data Science career? 

Apoorva: Be curious. Get more exposure to solving the problem statements. You can target doing one project/month or something per your role. But keep going on this journey.

AV:  If someone is transitioning from another field and moving into Data Science – what should be their approach?

Apoorva: I would like to share a few steps I followed in my journey.

1. Data science is a vast field. Select the role you are aspiring for.
2. Research and create a list of topics to get the relevant knowledge for the role.
3. Find/Enroll in a course or go through youtube to understand the topics along with hands-on.
4. Once the base is ready, find small projects of your interest area. 
5. Find a suitable database(on kaggle) and start working on the project.
6. Try and maintain the portfolio over git, which could be shared over resumes.

AV: What is that one mistake that helped you improve at work?

1. Grabbing Opportunities: Often, I used to decline the client’s requirement, which was not known/done before. We always tend to say no to something which we are not familiar with. But I had learned to grab these opportunities to get out of my comfort zone to enhance learning and experience, which is part of growth.
2. Ownership: Shifting responsibility is very common when things go wrong. I learned to accept my mistakes gracefully by taking responsibility.

AV: Would you like to share resources to help freshers/ people transitioning into the DS industry?

1.  Start with Learning Python: Python for data science by Jake VanderPlas
2. For Statistics: Mathematics for machine learning by Marc Peter Deisenroth
3. For Machine Learning: Practical Machine Learning with Python by Dipanjan Sarkar

These are the core books for reference. As you proceed, various blogs and articles will guide you.

Conclusion

In this interview, Apporva Kakde, a data scientist at TCS, shared her journey and experiences in the field. In this interview, she highlighted her challenges during the transition from a developer to a data scientist and emphasized the importance of problem-defining and solving skills. She also discussed a challenging project she worked on and the impact of her hobbies on her personal growth and career. Finally, she shared some resources and recommendations for staying up-to-date with the latest developments in the field. Overall, through this interview, her insights provide valuable guidance for aspiring data scientists looking to succeed in this field.

If you wish to read more such engaging and inspiring interview stories that shed light on the journey of young professionals, then keep checking our website for regular updates.