With more than 16 years of experience, Supriya Singh Raman is a Data Scientist proficient in designing and developing statistical and predictive machine learning models for identifying patterns and extracting data insights. She is currently the Vice President - Data Science - Corporate & Investment Banking at JPMorgan Chase & Co. 

Can you tell us about your AI journey? 

With sixteen plus years of Technology Leadership experience, I have led organizations for Statistical and Predictive Model development, Text Analytics, Data Science, Machine Learning and AI, Product Engineering, Intelligent Automation, Design Architecture, Quality & Assurance, and People Engagement etc. I have been exposed to most technologies like Data Science, AI/ML, Cloud, RPA, BPM, UI/UX, Java, .Net, Microservices, Data Engineering, Integration Services, Web Technologies, Mainframe etc. 

My AI journey started in 2013 when I was recruited for Payment Remediation Analytics. I slowly gained hands-on problem-solving experience at all levels of business. I engaged in business problem solving using Artificial Intelligence & Machine Learning through data analytics. I also got certified in Machine Learning, Data Science, Artificial Intelligence, Text Analytics, Cloud Technologies, Deep Learning, Agile and Product Owner. 

In my career, I have been developing & leading top-performing teams of Data Scientists and Machine Learning experts who solve data-driven challenges through AI & ML Solutions, Knowledge Graphs, Big Data technologies and Analytics Storytelling. I am a data leader directing a global team of data scientists and engineers, delivering end-to-end ML business solutions in Corporate KYC and Client On-boarding.  

I am the winner of Analytics India Magazine Top 10 Indian Women Data Scientist 2021. My passion as a technocrat is to pioneer Augmented Reality, Text Analytics, Cloud Computing, Data and Edutainment of Digital Transformation in the Organizational Transformation journey. 

What is your area of expertise in AI, and what made you choose it?     

My area of expertise is mainly AI-based Text Analytics. A comprehensive understanding of our customers is key to achieving core business goals. This is across domains, whether banking, Healthcare, Retail or any other business.  

Text feedback is the closest we ever get to a 1:1 conversation with every customer, every citizen, and every employee. In free text, our customers tell us what they care about and why unconstrained by the questions we decided to ask them. It's where the customers get to decide what's most important. We can gain actionable insights from every email, social media post, chat message, and survey, which can be leveraged to improve customer experience.  

Also, there has been significant growth in the volume and variety of data because of the accumulated unstructured text data. As a result, companies are now relying on technologies like text analytics and Natural Language Processing (NLP) to make sense of such massively collected data. 

Some common applications I worked on are Social Media Analytics, Sentiment Analysis, Chatbots, Market Analysis, Competitive Intelligence, fraud detection, customer care service, risk analysis etc. 

Also, my most exciting involvement with this field is for research work with several advancements in deep learning techniques in text generation. I am involved in my initial talks and will soon enrol for research. 

Can you say something about your current role and your handling projects?    

I am working as Vice President, Data Science in KYC & Client Onboarding pillar of the Corporate and Investment Banking (CIB) division of JPMorgan Chase.  

I lead a global Data Science team that enables better business decisions and improves our Corporate KYC platform and user experiences through data insights, predictive models, experimentation, and analytics. My team is a critical partner in delivering insights that inform both business strategy and feature/ framework development roadmaps. In my role, I am responsible for defining, leading and evangelizing analytics solutions leveraging Data Science offerings. I deliver thought leadership and innovation in process, technique, and implementation. 

Most use cases demand text analytics, and we use NLP and Deep Learning techniques. We provide ML/AI-driven solutions for onboarding experience, serving consumer preferences for payment platforms, fraud detection, anti-money laundering etc. My role requires directing end-to-end model development and deployment lifecycle, accomplishing mission-critical user-centric deliveries using scrum methodology.

Describe some challenges you have faced in reaching where you are now.   

To dream big while belonging to a small town, strict conservative family is itself a dream. We lack social and family support, vision and guidance. However, my parents focused a lot on my studies. Therefore, I set very tough targets for myself on my life objectives to achieve what I have today. 

As a woman, we face the daily challenge of solving work-life balance. I have a lovely 11-year-old son. My husband and I believe in switching our roles to support each other. Indira Nooyi explained in her interview, "As a woman, the biological clock and the career clock are always in conflict. When we have to build our careers, we get married and have a kid. As we step into middle management, our kids become teens and need more of our time." Every working woman can relate to this. We are always split between work and life. There is no more work-life balance. All we can do is work-life integration. 

Do you see enough female leadership roles in corporates? In your opinion, what should change? 

In recent years, there have been calls for greater gender equality while enhancing the need to close the gender gap. However, despite small gains in recent years, female leaders have less representation in the current scenario. I have attended many meetings in a room full of men. 

I can see a lot of support from the organization and workplace culture. Many CEOs have made gender diversity a priority. Women managers are assumed to be more empathic, innovative and engaged.  

One thing which should change is the women's attitude toward opportunities. As a woman, please stop battling with stereotypical mindsets, self-guilt and society's expectations. If you have an aspiration, bury your 'female' sensibilities and go get it, no matter what. Please remember that a giant leap is not needed to start – it's okay to take small steps towards your goal. 

Discrimination by AI is a genuine concern while ensuring data integrity - does this exist? If so, how can it be addressed?    

AI/ML-driven solutions are increasingly important for organizations seeking competitive advantage through digital transformation. Data Integrity and AI both need to be power trusted. We must design, develop, and deploy AI algorithms to meet ethical standards and eliminate bias or discrimination.  

Some common questions to be solved are Data Silos, Data Enrichment, tools and techniques used for Data Integration, Data Privacy and domain expertise of Data scientists. 

What do you want to say to women who wish to build careers in AI and other tech-related fields? 

Be Brave, Be Humble, Be Fearless. 

Data Science/ AI field is flooded with opportunities. Get it. Show confidence, and live the life you always dreamed of.