With over 20 certifications in Data Science and AI from reputed companies and institutions, Yaasna Dua is one of the top upcoming women data scientists currently working at McKinsey & Company. Yaasna is known for her quick designing skills while conducting data science experiments with strong mathematical fundamentals and programming skills.
Can you tell us about your AI journey?
After graduating from Delhi College of Engineering (DCE), I started my career as a Java developer. Seeing the impact of AI/ML on the breadth of industries like Healthcare and Finance to Human Resources attracted me to pursue a career here. I started with Andrew NG’s courses on Machine Learning, where I saw the potential of AI/ML to create an impact on a scale by delivering reliable solutions to problems impacting businesses and people.
Data science is a multi-faceted skill set. I started my upskilling journey by reading articles, participating in hackathons, getting recognized data science certifications, and listening to talks from global AI leadership. I believe my experience in hackathons and my credentials helped me break into my first Data Science role at Publicis Sapient. That kick-started my AI journey and paved my way to work as a data scientist in Naukri.com, where I handled the full life cycle of a data science project, from gathering and cleaning data to building models and deploying ML systems. I then joined my current firm McKinsey & Company, where I have closely worked with clients to solve their employee lifecycle problems using data-driven decision-making.
What is your area of expertise in AI, and what made you choose it?
My key motivator has been a real-life large-scale impact. I developed expertise in Recommendation Engines and NLP while working at Naukri.com, where I built job and course recommendation engines, helping 6 million + people per week in their job search. At McKinsey, I continued making scalable Data Science Products. Apart from managing the life cycle of ML projects, my area of expertise expanded to stakeholder management and data-driven decision-making. After working as a data scientist for eight years, I have realized that before building ML products, it is important to facilitate a change in leadership mindset from intuition-based to data-driven decision making.
Can you say something about your current role and your handling projects?
In my current role at McKinsey, I manage projects which help our clients make data-driven decisions about the Employee Life Cycle. I also work on creating data science products which facilitate long-term Strategic Workforce planning, gathering Talent Market Intelligence and benchmarking clients’ talent against their competitors at scale. These products, in 4+ years, have managed to touch 400+ companies across multiple geographies.
Describe some challenges you have faced in reaching where you are now.
I have been lucky that my family and all my employers have been supportive and encouraged me to pursue opportunities that have facilitated my growth as an individual and as an AI professional. However, one of the biggest challenges I faced was a lack of formal support network, sponsorship and coaching. For upskilling, I took MOOCs and leveraged LinkedIn to connect and follow industry thought leaders.
Do you see enough female leadership roles in corporates? In your opinion, what should change?
I was reading recent research by McKinsey, which stated that women’s representation in the workplace at senior leadership positions is almost 1/3rd of that of men. The baseline in the funnel keeps decreasing. As for 100 men promoted, only 86 women are encouraged. I think the first …….
Source: https://indiaai.gov.in/article/yaasna-dua-data-science-specialist-mckinsey-company