Kavita is an Analytics leader with 12 + years of core hands-on experience having an excellent track record on Presales, Partner Management, Analytics Delivery, and Team management across domains in World-Class Organizations. Currently, she is heading the Data Science function at Infinite Sum Modeling. She is a Chemical Engineer by education followed by a Masters (Eco) from IGIDR. She is a seasoned analytics professional with work experiences across companies like Fair Isaac, Experian, Accenture, Infosys, and Vodafone. Her vast experience in domains like Banking, Insurance, Telecom, Fraud, and Risk Management gives her the right kind of diversification. She has published papers in areas of Financial Econometrics and Social Media Analytics. She has been an esteemed speaker at various national seminars on Analytics. Her passion for Analytics and learning drives her to explore newer technologies and innovations in Analytics space. She is currently leading the capabilities of the firm in the areas of data science and analytics training as well as new business development in several areas that include data science, business analytics, Artificial Intelligence, Data Mining, Machine learning, blockchain, robotic process automation, econometric modeling, CGE modeling, policy/business strategy analysis, among other areas of interest to the company.
Alex has 17+ years’ experience developed across a number of industries and domains, including Federal and State government, Insurance, Asset Management, Banking (Investment and Retail), Consulting, and Academia. He has expertise in leveraging Data Science/AI to deliver impact and change, by developing and managing high-performance teams, and via strategic advisory and technical expertise. Alex has recently been recognized as one of the Top 10 Analytics Leaders in Australia by IAPA (Institute of Analytics Professionals of Australia).
You can follow Alex on Twitter (@DrAlexAntic) or his blog (https://impartiallyderivative.com).
Noriko Arai is the program director of an AI challenge, Todai Robot Project, which asks the question: Can AI get into the University of Tokyo? The project aims to visualize both the possibilities and the limitation of current AI by setting a concrete goal: a software system that can pass university entrance exams. In 2016, Todai Robot achieved the top 20 percent in the exams and passed more than 70 percent of the universities in Japan. She is also the program director of Researchmap Project to build a platform for researchers to manage their research activities. The inventor of Reading Skill Test, in 2017 Arai conducted a large-scale survey on reading skills of high and junior high school students with Japan’s Ministry of Education. The results revealed that more than half of junior high school students fail to comprehend sentences sampled from their textbooks. Arai founded the Research Institute of Science for Education to elucidate why so many students fail to read and how she can support them.
Gunjan has been working in the industry for 3+ years and has a background in Mathematics. Currently, she is working with the Fraud Team in the Gopay (Gojek) Data Science team. She can talk about statistical models with you all day long and can’t help but notice patterns everywhere in her life. Along with her day job, she also mentors aspiring young data scientists. She currently a mentor at springboard.com for their course Data Science Career Track.
Saptarishi is Sr. Analytics Consultant, India, supporting the SAS Platform product lines. In his current role, Saptarishi works with customers to collaborate with multiple stakeholders to ideate and build product prototypes for various business demands which can become a revenue potential. He has worked with customers in Financial Services, Insurance, and Manufacturing.
Saptarishi is passionate about discussion and designing solutions in the area of Machine Learning, Deep Learning, and Data warehousing.
As a data and information ethicist, Theresa uses creative, compassionate, and contemplative practices to help communities build better digital and data futures. Building consensus through gaining and maintaining a community’s trust and implementing good practice to advance socially-just data policies is embedded in her work. Her award-winning work as an educator and researcher engages with the ever-evolving relationship between people and emerging technologies when working with data and making decisions. A social informaticist with a Ph.D. in Information Science, she served as inaugural Director of the Master of Data Science & Innovation program at UTS from 2014-2018, leading the development of a uniquely transdisciplinary and human-centered curriculum that continues to prepare graduates for the demands of the data science fields. Now working as a freelance consultant, Theresa contributes to government, industry, and NGO efforts advancing socially-just data policies, building processes for gaining and maintaining a community’s trust in data/AI use. She recently joined the Standards Australia Data Sharing Committee (IT-027-06 and JTC 1/SC 32/WG 6). Theresa also contributes to international initiatives related to data sharing via the International Science Council’s Committee on Data and as a Sydney Ambassador for Stanford’s Women in Data Science Network.
Natural Language Processing
Time Series Analysis
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