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One of the common misconceptions about data science careers – besides a hefty pay cheque – is that it involves working with data and using machine learning algorithms to build predictive models. While this is just a core aspect of the job, it is important to recognise that data science is a multifaceted field that requires a diverse range of skills, which goes beyond technical nuances. AIM recently sat down with Rupesh Khare, the global head of advanced data analytics and artificial intelligence at ABB, to gain valuable insights. Rupesh emphasised that a career in data science is both fulfilling and challenging—“rewarding but demanding.”
Rupesh said that passion for the role is the first filter. According to him, this role demands knowledge of statistics, mathematics, programming and technology. He believes that an honest evaluation of one’s skills in these subjects must be a starting point. “Following a trend is not a good enough reason to commit oneself to an industry where one may not belong,” said Rupesh.
The second is practice. Rupesh said that the ability to keep learning is the only response to the dynamic demand of this industry. “A periodic upgrade of skills and knowledge is the mantra of continued success here,” he added.
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Patience is the key differentiator. He believes that professionals in this field must understand that magic wands typically exist in fairy tales. “Unreal expectation on learning and rewards is the self-goal. A medium to long-term view of RoI is essential for sustained growth,” said Rupesh.
“I have had the opportunity to work with some exceptional data scientists during the last two decades. However, the proportions of unsuccessful stories are no less too. Many disappointments could have been avoided with cautious homework and honest introspections,” shared Rupesh, explaining that young talent must do a sense check before committing to the field of AI and analytics.
An Empathetic Leader
As the global head of advanced data analytics and artificial intelligence at ABB, Rupesh Rupesh currently leads the AI and analytics team to deliver cutting-edge projects to its customers across the globe. Prior to this, he worked in senior leadership roles at Optimal Strategix Group, HSBC India, Aon, Honeywell and others.
“ABB, with more than 130+ years of legacy, is a place of possibilities,” remarked Rupesh. He said that ABB’s commitment, culture and care make it easy for him to take up inevitable professional challenges.
“Leading a high-potential team is always exciting and full of mutual learning. We operate in the knowledge industry, and the main driver of the success here is an investment in your people,” said Rupesh.
He further shared that the investment depends on the situation at individual and collective levels. “However, the investment does not limit to knowledge and skills, but may also include emotions,” Rupesh added, saying that emotional quotient (EQ) has been a crucial dimension of people management. “EQ is the gateway to achieve together.”
As an empathetic leader, Rupesh believes that his role allows him to positively influence and touch people’s lives. “I believe that each person brings unique strengths to the table, and mentoring aids in nurturing people to be their authentic selves, unleash their full potential and help achieve their career aspirations,” he added, “I am also passionate about uplifting women in technology and have contributed to multiple D&I initiatives”.
Rupesh said that ABB’s AI and analytics team is positioned as a ‘startup’ in a Fortune 500 company. “We inherit the vision, legacy, ABB way, values and operating model. This foundation of ABB culture provides us with the base to further build a team culture of trust, collaboration and innovation,” he added.
ABB’s global AI and analytics team currently works on various use cases across four business areas and seven functions. This includes addressing business issues in marketing and sales, pricing, supply chain, finance, tax, controls, health and safety, and more.
The team said that the portfolio of the case studies is broader and deep. They have been leveraging multiple technologies to execute projects of varying complexity, where they are elegantly implementing technologies on both structured and unstructured data.
In the last five years, ABB has delivered more than 70 projects of various sizes and complexities across domains and geographies. “After establishing an initial rapport and trust through Proof-of-Concepts, the customers are now shifting towards multi-year projects and embracing AI or Deep Learning based advanced solutions,” shared Rupesh Khare.
He said that these solutions were aimed to address complicated use cases providing the stakeholders with tangible or intangible benefits. “It is not possible to quantify the benefits of all analytics solutions. Sometimes, the outcomes of the solutions do not impact any operational KPIs but they act as an enabler in effective decision making,” said Rupesh, sharing that in these circumstances, the benefits of analytics are latent, empowering the organisation to improve the operational ecosystem.
Analytics here is an outcome of an efficient collaboration among business, IT and data science teams. The focus of the data science team is primarily on the solutions to the business use cases, instead of just building ‘models’. “Unlike the many other companies in this space, a data scientist here works on the entire life cycle—data management, building and testing models and solutions—of the project. This provides them with a full view of the project and also reduces the occurrences of the slips due to change of hands at each stage of the project cycle,” said Rupesh.
At ABB, the data scientists are said to continuously invest in their regular upskilling and hence the effort on the training is critical. “We are keeping pace with the uptrend in the expectations from our customers. Hence, the solutions in their hands should provide self-service analytics with more autonomy to use the solution,” said Rupesh, further adding that this objective guides the team to make a shift from the ‘Project’ to the ‘Product’ and drives them to develop cloud-based products based on end-to-end automation of the process.
Additionally, the team represents itself globally through conferences, workshops and technical publications at various levels.
What Sets ABB Apart?
Today, most organisations have not been very agile with the storage, infrastructure and usage of data. Not many large organisations have had a good process and policy on data management, thereby leading to piling up multiple legacy databases, ineffective data collection and storage, and resulting in underutilised data for decision-making. In addition, the infrastructure historically used for data management has also not been at pace with the highly dynamic digital transformation.
“We at ABB are strategically moving on the digital transformation journey. We are objectively maintaining the balance among customers’ demands, fast-changing digital specs and internal resource inventory,” said Rupesh, adding that the company strategised a flexible data strategy and carefully selected the forward-looking technologies.
“In order to receive quick dividends of the endeavour, an organisation-wide drive to crystallise the awareness of analytics and associated advantages proved to be a catalyst,” he shared.
“Data Science services are growing quickly. Our vision is to leverage Analytics and AI for continued leadership in the global market. We are steadily adding value to our customers through sustainability,” said Rupesh.
In light of that, ABB’s vision and mission would be to drive towards a world-class data science team that can solve complex business problems and innovate, in alignment with the company’s goal.
“As a global leader, I have constantly been involved in onboarding bright minds from diverse backgrounds such as statistics, Mathematics, Engineering, Economics, MBA and more, while we also upgrading and upskilling our present workforce,” said Rupesh, “Additionally, we are striving for new technology adoption in our team such as IOT, Cloud Services, that provide hinge support to our regular work.”
Rupesh believes that having witnessed a long journey in the analytics industry, their unconventional approach and vision have predominantly shifted from project to product, leading to wider customer and geographical coverage.