Accenture’s Ankita Shrivastva talks to us about what it’s like to work in data and AI, and gives advice for women who want to break into the space.
According to Ankita Shrivastva, her entry into the data and analytics space was “unplanned and incidental”.
“Having worked in investment banking and then in part of Accenture’s financial risk management consulting team back in India, I was suddenly looking at a prospective move to Ireland with my partner,” she explains. “An opening in the local data and analytics practice in Dublin caught my interest and I applied for the role and got it.”
Shrivastva says her background in professional strategy and consulting, along with a grounding in maths and statistics, helped her secure the position. “My new role gave me the opportunity to use these fundamental skills in numbers and data across a wide range of clients and industries other than banking, unveiling limitless potential of data in helping clients from day-to-day decisioning to longer-term strategic imperatives.”
Now, Shrivastva holds the position of data science manager with Accenture’s data and AI practice.
‘AI and analytics is such a vast field today that it gives people the freedom to chart their own course’
What were the biggest surprises or challenges you encountered on your career path in AI/analytics and how did you deal with them?
Coming from a corporate finance background, I was used to a very different terrain in terms of building knowledge and specialisation. Growth and learning there was more vertical – going deep into the fundamental concepts of finance. While the field is evolving, the pace of change is comparatively slower, and traditional concepts and practices persist. Data and AI was a completely different field in that aspect – nothing is stable in this field – technologies, tools, applications, everything is constantly changing and evolving, making previous knowledge redundant. Continuous upskilling in reaction to new technologies, methodologies and tools is crucial for sustained growth. Learning in this space is all about keeping up with latest innovations. Specialisations are limited and at constant risk of being made obsolete.
Was there any one person who was particularly influential as your career developed?
In the course of my career, I’ve been fortunate enough to work with some really exceptional people who have inspired me in different ways and shaped my professional trajectory. While I learned a lot about what lies behind their success stories from their working style, their commitment to continuous learning and resilience in the face of adversity; the one common thread without an exception among all these great women leaders was their remarkable capacity for empathy, a quality that defines their leadership.
I learned what leading by example truly means, observing their ability to navigate challenges with a compassionate understanding of team dynamics and individual strengths, celebrating their teams for any success, and motivating them in failure, all of which has been particularly impactful. As I progress in my career, I aspire to emulate this empathetic leadership style, recognising its potential to foster a positive and inclusive work culture.
What do you enjoy most about your job?
The best part of my job so far has been the constant change, and the variety of work I get to do as a data and AI consultant. The field itself is extensive – when thinking of utilising data at an organisational level, you need to think about your data strategy, your data architecture, data warehousing, cloud strategy, data privacy, data governance framework, and then of course using that data. From data analysis to visualisation for reporting and decision-making, from developing and deploying simple predictive models to using more complex language-based models – there is always something new and exciting to learn.
And the role itself – consulting is all about donning many hats. Problem-solving, people management, sales, delivery – there is always a new challenge to keep things exciting!
What aspects of your personality do you feel make you suited to AI/analytics?
I think it’s a cliched answer but true nonetheless – analytics is suited to people who enjoy abstract problem-solving, who are thinkers, who enjoy puzzles. Additionally, an eye for detail and a methodical approach certainly helps in this space, as do effective communication skills that help foster collaboration and understanding in a team set-up when working on a complex data problem.
What can people expect from career progression in the AI/analytics industry? Did your current employer support you with this? If so, how?
AI and analytics is such a vast field today that it gives people the freedom to chart their own course. You can choose to deep dive into an area of data – such as data governance, data management, data privacy, or become a data scientist working with ML models. You can take on the more technical roles of data engineering, data architecture, or take a more holistic advisory role in consulting the client on their end-to-end data and AI strategy. You can choose to work for a consulting firm like Accenture and help solve problems for clients across industries or be part of an organisation’s internal data teams.
The field of AI and analytics offers many career paths and is only going to grow as we head towards a future underpinned by data and AI. In my role with Accenture, I have been fortunate enough to be given the opportunity to experience the whole value chain of data and AI to get a more holistic view of how organisations can tap the huge potential of their data in the most effective way.
What advice would you give to those considering a career in AI/analytics, or just starting out in one?
During my time with Accenture’s data and AI team, I have often come across women hoping to start a career – or make a career change – into data and analytics, but often lacking the confidence to do so, assuming they lack the necessary qualifications or technical proficiency. My advice specifically to them is not to underestimate themselves. Data and AI, as a field, benefits from many different backgrounds and experiences. While technical skills underpin many roles in the space and should be developed consistently, logical reasoning, strategic thinking, industry knowledge etc play an important part as well. My advice is to build a network of mentors and peers who can be your guides in your career journey. The support and wisdom of those who have walked this path before can be invaluable. But, equally, trust your unique perspective and voice. Your diversity of thought is a strength that will set you apart.
For those women who are interested in a career in data science, I would highly recommend participating in the Accenture Women in Data Science (WiDS) programme: an accelerator programme targeted specifically towards women, to gain first-hand experience of what a career in data science will look like, through problem-solving using data, workshops, career stories and the opportunity to meet and network with other women with the same career interests. Applications for our 2024 programme are open from 14 February to 7 March.
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