Dr. Irvan Bastian Arief, VP of Data Science & Machine Learning Engineering, tiket.com

Dr Irvan Bastian Arief is an award-winning, PhD-qualified digital executive, leader, machine learning algorithms creator and strategist with over 16 years of commercial experience in technology, digital and data-related domains. He is the recipient of the CIO100 Awards: Next CIO (2023), the 2022 Outstanding Taiwan Alumni of the Year and the 2020 Innovation and Entrepreneurship Award from Australia Global Alumni and the Australian Embassy for Indonesia. He used to work with General Electric (GE), TSMC, and Tokopedia. At present, he is both the Vice President of Data Science & Machine Learning Engineering and Vice President of Tech Infra Platform at tiket.com and also the lecturer at Bunda Mulia University.

Recently, in an exclusive interview with Digital First Magazine, Dr. Arief shared his professional trajectory, one key data science technology that interests him, insights on the future of data science market in the upcoming years, the secret mantra behind his success, future plans, pearls of wisdom, and much more. The following excerpts are taken from the interview.

Dr. Arief, please walk us through your journey into data science and machine learning?

From my earliest memories, the allure of gaming has been a constant companion. The way a video game’s digital realm comes to life, driven by a computer’s seemingly intelligent responses, has long held a mesmerizing grip on my imagination. This fascination laid the groundwork for my foray into software engineering—a field where automation is not just a concept but a heartfelt passion. The marvel of orchestrating automated processes and steering the helm of digital transformation has been a driving force in my career. This journey naturally progressed to an exploration of artificial intelligence (AI) and machine learning (ML), realms where models possess the astounding capability to learn and operate autonomously beyond explicit programming.

When you were starting in the field, what kind of challenges did you face? How did you overcome them?

My earnest journey into the field commenced during my PhD studies, building upon a robust foundation in software engineering, data analytics, and business intelligence. Confronting the intricate mathematical equations embedded in high-calibre research papers emerged as one of my greatest challenges. To demystify these complexities, I returned to the fundamentals, dissecting each symbol, questioning its purpose, and exploring alternatives. This meticulous approach gradually built my proficiency. As I became more conversant with the language of mathematics, the essence of various machine learning algorithms began to resonate with me, transforming what was once daunting into something almost instinctive.

Please tell us about your roles and responsibilities as VP of Data Science & Machine Learning Engineering at tiket.com.

In my role as Vice President of Data Science & Machine Learning Engineering at tiket.com, I have the privilege of guiding the strategic vision and roadmap for our artificial intelligence initiatives. My responsibilities encompass overseeing the development of sophisticated AI and ML models that serve as the backbone for various verticals within the company, including accommodations, flights, and ‘Things To Do’ categories like attractions and events. A key focus of our division is to enhance customer engagement through tailored cross-selling, personalized recommendations, and search ranking optimizations, all powered by the cutting-edge capabilities of AI and ML. This approach is pivotal in elevating the user experience for each individual customer.

Additionally, I spearhead the R&D efforts within the company, ensuring that our AI and ML strategies remain innovative and effective. Beyond these responsibilities, I also hold the position of Vice President of Tech Infra Platform, where I oversee the technology infrastructure platform across the entire organization, ensuring a robust and scalable technological foundation.

What is one key data science technology that particularly interests you?

One key data science technology that interests me is “Machine Learning,” especially its subset, “Deep Learning”. Machine Learning is a pivotal technology in data science. It enables computers to learn from and make decisions based on data. This technology is behind many modern conveniences and innovations. Deep Learning, a subset of machine learning, is particularly fascinating. It involves neural networks with multiple layers (hence “deep”) that mimic human brain functions to some extent. This technology powers complex tasks like image and speech recognition, and it’s the core behind many AI advancements, including natural language processing models like OpenAI GPT-4 and Google PaLM2.

In today’s digital era, what is the biggest data science mistake you see enterprises making?

In the realm of large-scale enterprises, a prevalent and critical error in the approach to data science looms large: the premature commitment to AI and machine learning solutions without a clear articulation of the underlying business problem. While undoubtedly transformative, these advanced technologies are merely instruments in the broader orchestration of problem-solving. Yet, some corporations, eager to brandish their cutting-edge credentials, rush to adopt these tools indiscriminately. The allure of appearing ‘in vogue’ with AI and ML often overshadows the essential need to first identify and understand the specific business challenges at hand. The accurate cautionary tale here is not the hesitance to embrace AI and ML, but rather the hasty, ill-suited application of these technologies. It’s a misstep that can transform a potentially wise investment into a costly misadventure.

You have worn multiple hats in your extensive career and have been a recipient of prestigious awards and accolades such as Next CIO (2023), the winner of the 2022 Outstanding Taiwan Alumni of the Year and the 2020 Innovation and Entrepreneurship Award from Australia Global Alumni and the Australian Embassy for Indonesia. What is the secret mantra behind your success?

In my professional journey, the cornerstone of my efforts has always been to make a significant impact — on the organization I’m part of, the wider community, and the nation at large. Within the organizational context, my aim is steadfast: elevating revenue, refining cost efficiencies, and enhancing the overall user experience. When it comes to serving the community, I take a multi-faceted approach. My commitment goes beyond delivering keynote speeches across various platforms. It extends into the academic sphere, where I impart knowledge and insights through teaching and lecturing at prestigious universities, including Monash University, RMIT University, and Bunda Mulia University. On a national level, as an ambassador of AI and ML, I am dedicated to promoting these advanced technologies across Indonesia. My mission is twofold: to foster understanding and appreciation of AI and ML within the country, and to cultivate a new generation of leaders in this field. This is all part of a larger vision — to position Indonesia not just as a consumer in the world of AI and ML, but as an influential creator and innovator in these transformative technologies.

What is one of your favorite parts of the workweek? How does it encourage or inspire you? Do you have a favorite way to recharge during the workday?

The highlight of my workweek invariably unfolds within the dynamic atmosphere of our team meetings. It’s in these collaborative arenas where a symphony of ideas is exchanged, and the blueprints of our projects begin to materialize. There’s a palpable sense of ‘iron sharpening iron’ as each colleague, through their unique insights and expertise, contributes to the collective sharpening of our team’s acumen. This environment is a crucible of inspiration, fueled by the vibrant exchange of energy and creativity among peers. As for recharging during the hustle of the workday, I find my solace in stepping out into the open air, embracing a change of scenery. This simple act serves as a mental reset, a moment of reprieve that reinvigorates my focus and clarity.

In your academic or work career, were there any mentors who have helped you grow along the way? What’s the best piece of advice you have ever received?

In the unfolding narrative of my life, each chapter has been enriched by the presence of diverse mentors, each imparting unique lessons and insights. I have reached a stage where my own experiences and learnings have equipped me to mentor others. While it’s not possible to reciprocate directly to those who have guided me, I am passionately committed to passing the torch of mentorship to those who follow in my footsteps. Among the many pearls of wisdom I’ve acquired, one stands out with resounding clarity: We judge ourselves by our characteristics, yet others judge us based on our behaviours. This seemingly simple observation holds profound depths, revealing the essential dichotomy of internal self-awareness and external perception. It underlines a vital lesson – the necessity of aligning our inner qualities with our outward actions. This alignment is not just a pursuit of personal authenticity, but a bridge that connects our true selves with the world, enabling us to be understood and valued not just for who we are inside, but also for the impact of our deeds in the outer world.

Where do you predict the data science market will be 5 or 10 years from now?

As we witness the rapid evolution of Generative AI, it’s becoming increasingly clear that the data science landscape is poised for unprecedented expansion. This technological revolution is set to create a plethora of specialized roles that delve deeper into the intricacies of artificial intelligence.  Presently, the field is predominantly occupied by data scientists and machine learning engineers, but the horizon is broadening.

Looking ahead, we can anticipate the emergence of distinct and specialized titles like AI/ML Specialists, AI/ML Scientists, and even more niche roles like Prompt Engineers and Generative AI Engineers. This burgeoning domain isn’t just growing; it’s heating up, with demand for these specialized skills set to escalate dramatically. We’re standing on the cusp of a new era in AI and data science, one where the depth and breadth of roles will reflect the complex, multifaceted nature of this rapidly advancing field.

Where do you see yourself in the next 5 years?

As the AI revolution unfolds, I am steadfast in my commitment to remain at the forefront of this transformative wave. As a fervent advocate for data and AI, my belief in the monumental impact of this technological transformation is unwavering. The potential for AI to significantly enhance human life is immense, and it’s a privilege to be an active participant in this journey of change. My aspiration is not just to witness this evolution, but to be a driving force, a catalyst that helps steer this technology towards its fullest potential in reshaping our world.

If you could give one piece of advice to a data science professional in the beginning of their career, what would it be?

If I were to offer a single piece of advice to a data science professional at the start of their career, it would be this: Embrace continuous learning and remain curious. Data science is a rapidly evolving field, constantly emerging new methodologies, technologies, and best practices. Staying abreast of these developments is crucial. This means not only refining your technical skills in areas like programming, statistics, and machine learning, but also developing a deep understanding of the industry you’re working in.

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