Building Impactful Decisions with Soudhakar Elumalai

"Data science is not just about algorithms; it's about transforming ideas into impactful solutions."?

These words resonate deeply with the career journey of Soudhakar, Head of Global Analytics at Heineken. Taking us through his?experience, he dives into the evolution of data science, from software engineering principles to navigating the complexities of cloud computing. Join us as we explore Soudhakar's wisdom on using Generative AI, empowering startups, and guiding aspiring data scientists towards success.?

Insights from Soudhakar’s Journey:?

• Transformation in Data Science:?

Soudhakar highlights the evolving nature of data science, stressing the need for a software engineering approach. He suggests that becoming a full-stack data scientist is essential, highlighting the importance of understanding both model creation and implementation for impactful solutions.?

• Choosing the Right Cloud for Data Engineering:?

While talking about Data Engineering, he said that selecting a cloud provider for data engineering can be challenging due to the similarity of services offered by Azure, AWS, and GCP. He suggested that starting with any of the three as they all provide strong solutions. Eventually, he added that the best cloud is the one that you're comfortable starting with.?

• Finding Inspiration from Impactful Projects:?

Soudhakar remembers his time at Flipkart and shared the Brand Index initiative, which was aimed at promoting healthy competition among platform brands. Despite its simplicity—a weighted average method—the initiative led to a positive shopping atmosphere for customers. Through collaborative brainstorming sessions, the team swiftly emphasized the value of impactful solutions over complexity.?

• Future of Data Science:?

He reflected on the evolving landscape of data science with generative AI, Chat GPT and other large language models. He predicts a future where traditional distinctions between specialities such as software engineering, data science, and MLops will blur. Instead, he envisions a collaborative environment where ideas would be executed seamlessly through interactions with chatbots.?

• Opportunities with Generative AI for Startups?

He saw how generative AI, particularly in e-commerce, can level the playing field for startups. He said it can reduce costs for content creation and advertising, making it easier for small brands to compete. Also, he sees the potential in streamlining processes in industries like CRM and SAP solutions, simplifying operations and customer engagement.?

Key Advice for Data Science Beginners:?

Soudhakar stressed about the importance of starting early and having a study plan, advising beginners to prioritize discipline and consistency. He suggested individuals create a routine to promote decision-making and achieve long-term goals. Additionally, he highlighted the significance of progressing every day, even if it means starting with fundamental concepts.?

Considerations for Hiring in Data Science:?

Soudhakar highlighted three qualities he looks for in candidates while hiring:?

1. Look for candidates with a strong study plan and demonstrated discipline in their learning approach.?
2. Prioritize consistency and progress over skills of advanced concepts.?
3. Assess candidates' ability to prioritize tasks and progress each day, even if there are delays in achieving milestones.?

Looking Forward:?

His insights provide valuable guidance for data scientists and anyone looking to succeed in their field. His journey highlights the importance of discipline, consistency, and adaptability in navigating this rapidly evolving field.??

The key takeaway??

Drive impactful solutions and shape the next generation with data-driven innovations.??

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