An Analytics and Business Intelligence Professional, Prof Hargreaves has over 30 years of experience in lead roles in multiple industries, including Pharmaceuticals, Healthcare, Fast Moving Consumer Goods, and Education. Currently, she is the Director of the Data Analytics Consulting Centre and an Associate Professor in the Department of Statistics and Data Science at the National University of Singapore.

Prof Hargreaves and her team has helped companies to generate economic, social, and scientific value from data using cutting-edge techniques and advanced data analytics strategies. She also provides hands-on workshops on Data Analytics for Customer Insights and Credit Risk Modelling to help companies keep up to date with new data analytics techniques.

Prof Hargreaves has worked with various leading companies like Pfizer, Novartis, MSD, Nestlè, MasterFoods, Goodman Fielder, Foxtel, Aztec, Cegedim Strategic Data, the National Health and Medical Research Council and the National University of Singapore (NUS) to make their businesses more intelligent.

Prior to her current role at the National University of Singapore, Prof Hargreaves founded her own company with a focus on helping clients understand their business challenges and problems to identify the relevant data that will help solve their business, problems. Over the years, she has also been the Chief of Business Analytics at the National University of Singapore, the Quantitative Methods Manager at IMS Health, a Statistical Modelling Analyst at FOXTEL and more.

Prof Hargreaves has a passion for solving business problems using analytics and machine learning techniques to build data-driven solutions. She speaks about how having faster and smarter business processes can empower organic revenue growth.

Some topics Prof Hargreaves speaks about:
• Knowing Your Customers with Data
• Managing Risk Strategies using Data Modeling
• Solving Real Business Problems with Data Analytics
• Data Privacy in the Age of Data - How to Use Data Safely
• Deep Learning - Building Efficient Data Models
• Women in Tech: My Journey as a Data Scientist