Meet Vaibhav, Senior Data Scientist
By Vaibhav Kherde
About Me.
Hello, I’m Vaibhav Kherde, a Data Scientist specializing in Generative AI and Machine Learning. With 8+ years of experience, I have a strong foundation in healthcare data analysis, my expertise extends to developing and deploying Generative AI models for tasks like text generation, image generation, and creative applications.
Can you talk a bit more about your background?
My diverse background blends my passion for data science with hands-on experience specializing in consumer knowledge and strategic insights. I began my journey by enrolling in specialized courses and certifications, where I developed a strong foundation in data analysis, machine learning, and statistical modeling. Over the years, I’ve been fortunate to work extensively with image analytics, text analytics, and large language models, gaining valuable experience in these areas. Additionally, my exposure to industries like healthcare and insurance has enriched my understanding of how data science can drive meaningful insights and solutions. Overall, my background has equipped me to tackle diverse challenges in the field of data science, and I’m excited about the opportunities ahead to leverage data for innovative solutions.
What did you want to be when you grew up?
I was always fascinated by technology and how they were shaping the world around us, from smartphones that make us smarter to gaming consoles that console us after a long day! This fascination fueled my curiosity and desire to understand the inner workings of computers, software, and emerging technologies. As I progressed through my academic journey, my passion for technology deepened, and I realized that pursuing a career in computer engineering would be the perfect avenue to channel my interests and skills. While my childhood aspirations may have been more focused on technology and problem-solving, they eventually lead me to the exciting field of data science.
What is your DS specialty and how long have you been doing it?
My specialty in data science revolves around machine learning, artificial intelligence, statistical modeling, and machine learning operations (MLOps). I’ve been actively involved in these areas for 8+ years, honing my skills and expertise through hands-on projects and continuous learning. Recently, with the advancements in generative AI, I’ve been particularly excited about its potential to transform various industries. I’m enthusiastic about further expanding my expertise and making it my specialty to drive groundbreaking solutions and advancements in the field.
What do you do day to day?
My day often starts with checking emails, and updates from the team. I also participate in sync-up meetings where we discuss progress, goals for the day, and any blockers with my team ensuring alignment. A significant portion of my day is dedicated to writing code and developing software solutions. This could involve working on new features, fixing bugs, optimizing code, engaging in code reviews, or implementing algorithms based on project requirements.
As we work in agile, I attend meetings such as sprint planning sessions, design reviews, and technical discussions. These meetings help in coordinating efforts, resolving technical challenges, and aligning with project timelines. Toward the end of the day, I summarize the progress, update task boards or project management tools, and reflect on accomplishments, and lessons learned.
How do you keep your knowledge current?
Staying updated with the latest advancements and trends is crucial for any data scientist in the ever-evolving world. Here’s how I keep my knowledge:
- Continuous Learning
- Hands-On Projects
- Following Industry Blogs and News
- Participation in Workshops and Conferences
Furthermore, I regularly engage in self-directed learning through online platforms and industry resources to stay updated with the latest advancements in data science.
What’s your top tip for anyone who wants to enter the field?
When I started in data science, I was overwhelmed by the wide range of technical skills it requires, including efficient programming, statistical analysis, machine learning, data visualization, and big data technologies, as well as mastering these skills to apply them effectively.
But always remember, every challenge is an opportunity to learn and grow. Rome wasn’t built in a day, and neither is expertise in the field of data science. Always take small, deliberate steps and develop your skills gradually over time. Each step, no matter how small, contributes to your growth and progress in the field.
Apply your knowledge by working on hands-on projects. Explore a wide range of tools, techniques, and methodologies and start with small problems and gradually tackle more complex ones.
My key suggestion would be to connect with peers, mentors, and professionals working within the data science community. Engage with them any chance you get in data science meetups, forums, and online communities, share ideas, collaborate on projects, and gain insights from others’ experiences.
What do you like most about working at Haleon?
Teamwork is a cornerstone for every organization’s success. Haleon has provided me with a collaborative environment where team members openly share ideas, knowledge, and expertise. The one aspect that I adore above anything else is working alongside experienced professionals, and I am grateful for the opportunity to learn from these experts in their respective fields. I believe their mentorship and guidance will play a crucial role in my growth and development, making me feel privileged to be part of such a knowledgeable team.
