Business decisions are greatly influenced by the analytics and insights derived from the data. The predictive and prescriptive analytics are the current trends of the business sector and are helping businesses in reducing their costs and optimizing profitability. According to Fortune business insights report on Machine learning market size, the global machine learning (ML) market is expected to grow at a CAGR of 38.8% in forecast period from 2022- 2029. Due to the growth in the data science industry, there is a continual need for talented people in this field. AI job postings have significantly increased across all industries, representing between 2-3% of all job postings in 2020. There are not enough data scientists searching for jobs to fill demand and gap has been getting wider in recent years; in 2019 there were ~1,100 job postings for every ~200 searches by candidates. The bargaining power of existing data scientists is therefore increasing. Retaining expert team members is one of the most important goals for any company that has invested heavily in training their data science team.
Since the beginning of ABI's D&A journey in 2016 until today, we have been growing our Data Science team to a world-class level. ABIA team has already made an excellent start in delivering $1B of profit uplift, and many impactful use cases. The key to success is to implement a few strategic practices that will enable your Data science team to scale and retain the talent you have. The purpose of this AI core talk session is to discuss and analyze some of the key strategies and go in-depth into each one.
Rai Rajani Vinodkumar
Global Director - Data Science Guild Lead, AB InBev
Mathematician & AI/ML Digital transformation leader excelling in Re-Imagining Business Processes with AI/ML, demonstrating possibilities with AI and shaping roadmap to scale. Rajani has established herself as a top innovator and has a proven track record in blending latest tools and technologies with advanced AI/ML methodologies in addressing some of the most complex business challenges. Her innovations have led to several AI assets and accelerators that drive agile solution development predictable outcomes in a scalable fashion.
As a distinguished director scientist, she leads the Global DataScience practice at AB InBev. She keeps the team of Data scientists thriving through focus on building expertise, designing and rolling out best practices and channelizing them to conquer unsolved problems and developing reusable assets. In addition to implementing AI/ML solutions across multiple analytics products, her team also implements feedback loops to continually improve algorithms for marketing, sales, and customer service operations across the globe.
Rajani holds a Master degree in Mathematics & Scientific computing from TU Kaiserslautern, Germany and from IIT Madras, India.