Artificial Intelligence (AI) has moved from a niche topic to a powerful internet dominant technology. With new advances every day, AI is creating new business opportunities and breakthroughs. Businesses have caught on and are investing more and more to turn their data into competitive advantages, from operations to market intelligence. This in turn fuels a need for more data science and AI-related roles in the workforce. For those looking to dive into the world of AI, the time is now.
As Vice President & Global Head of Analytics Operations at Evalueserve, I was recently named one of the top 50 AI leaders in India in 2021 by the Analytics India Magazine, a leading publication promoting analytical ecosystems. My team specializes in data advisory, data solutions, data science, and last-mile solutions which helps companies by providing end-to-end solutions from ideation to implementation. Certainly, the award is a by-product of all our collective efforts.
I began my journey at Evalueserve as an advanced analytics leader while the team was still small. In the last few years, we grew at an exponential pace mainly driven by our ability to scale, innovate and be flexible. Our ability to program manage end-to-end efforts in building up AI models and productionize each of them in different technological environments placed us in the league of Top 10 AI service providers.
I would like to share some tips with you based on those experiences. A career in AI is rewarding and full of innovation and excitement, and we are always on the lookout for more talent. For those looking to kick-start their career in this field, the following suggestions may help you get that dream job.
1. Find Your Niche
Once you’ve settled on the AI journey for your career, it’s time to do some research. Like any career, there are different roles in the workplace and it’s important to familiarize oneself with them.
One role is that of a business consultant, someone who understands the domain, who can articulate and conceptualize the business problem. They work with customer teams to come up with issue trees, which could be based on what is available from a data standpoint at the customer premises and the need to solve the business problem. Consultants help in taking unstructured problems and create smaller modules to help in structuring the solution.
The second role is that of a data engineer or data solutions specialist. These roles vary and deal with different aspects of data harmonization — integration, data research, transformation, understanding the data governance, quality assurance, etc. With the advent of big data and cloud, the companies are revamping their data architecture to drive the foundational layer for digital transformation.
The third role is of a data scientist who diagnoses the issues at hand and uses different problem-solving approaches like – predictive, prescriptive, machine learning, deep learning approaches to come up with the right algorithm to solve the problem.
The next role is of a BI developer who determines how the data could be consumed into different applications to be productionized at a user level. The user report could be consumed from an executive, operation, and or a tactical level.
Lastly, there are program managers who are responsible for project governance and the storytelling aspect of the business solution. Their jobs revolve around the presentation of the data in the right context so it can be easily understood by the end user.
So, to summarize there are different jobs you can pick from in this field, but they are interchangeable as you grow. Depending on what you like, you can build your career as you move along.
2. Understanding What Companies Want
There are three dimensions to what we look at in a particular team member and how they grow; mindset, skillset, and toolset. First is mindset, which is how they understand or grasp the physical business context, or the domain part of it. Next is how they apply the models and other pieces, and finally, third, there is the technology part of it, which is a toolset. How you capture all three pieces determines your success as a full-stack AI professional.
Apart from the basic qualifications that enable someone in their career field, pay attention to how you test your capabilities and innovate. Can you generate new ideas, offer out-of-the-box thinking, and solve problems?
At Evalueserve, we tend to give people open-ended problems – even our job candidates. We gauge how would they behave in a particular situation and how would they respond to challenges. There are no right or wrong answers, but depending on the situation and its constraints, we look at how the person can craft a solution.
What we look for and need is someone who can think outside the box. In AI work today, we see conventional problem solving may not be the last or easiest way to address a challenge.
The complex nature of data is always evolving. If you can think in terms of where you can utilize one part of the solution to address a different issue that has similarities in nature, then you create unique, anomalistic solutions.
3. Be Adaptable to Different Technologies
When new AI professionals start, they have a certain toolset, and that may include addressing one solution. Within the company, we have achieved a technology agnostic portfolio because our different customers use different kind of tools.
For us to rely over on one kind of technology would not suffice. So, what we look for are people who can adapt and evolve.
Within the company, we have a training and learning initiative, which we call the einstein™ Learning Platform. einstein™ helps people master open-source courses curated within the company to build up technical capabilities in different directions. This platform along with peer group learning, helps a person learn from different dimensions, which they can utilize in their everyday problem-solving work.
4. Stay Curious
A thirst for knowledge will help you stay ahead, and the easiest way to fuel that thirst is to ask questions. At our company, we follow a flat hierarchy which has really helped newcomers to be more open and inquisitive. During our brainstorming sessions — we follow a simple rule – No questions are silly questions.
Whether you’re on your job search or just landed a new role, don’t forget to ask questions. Curiosity is encouraged, it fuels innovation and that’s what is needed to succeed in this industry.
5. It’s Okay to Not Know Everything
So, you got the qualifications and certifications. But maybe you’re still not sure if you know everything. That’s okay, you don’t have to know everything when you start. Most companies like Evalueserve coach and train you, too.
A lot of people focus on just learning technical pieces, so they are good in coding or in math. This helps them become good AI professionals but something we want to see the industry encourage is domain learning or industry learning. It’s important to know the nuances of a particular industry, but what goes a long way is translating findings and insights to your customer.
When someone new joins our team we encourage each person to become true full stack AI professionals. We mentor and nurture them. We encourage AI professionals to do more than just focus on a particular trait. How can they start focusing on other aspects of the AI stack over time? How can we groom and coach them so they can become much stronger in different areas?
One thing to remember is you will learn along the way. So young professionals or those switching careers that are intimidated by job descriptions, I advise them to apply for positions they qualify for even if they don’t entirely match every job function listed. You will pick up the rest through your experiences.
Now that we’ve covered some insights on what to look for in terms of a career in AI, it’s time to make that move, and find the right opportunity and work environment for you. A good leadership and work environment that boosts your career is just as important as your skillset. I hope you will consider Evalueserve, too! We offer candidates more than just a job they will flourish in, we help them get exposure to teams with diverse backgrounds from all around the world.
Good luck and happy job hunting!
