Talk Summary: Data Science is an amazing and innovative space to work in, and its applications have changed our daily lives for the better. Unfortunately, this doesn’t make it immune from issues relating to bias and a lack of diversity. In a world where more and more processes are automated by AI, ensuring the algorithms are unbiased has become essential for society. We will look at different types of biases that occur in data science, their real world impact, and things to help mitigate them.

Bio: Divya is a Data Scientist at Digitas UK. Recently she’s been working on a project involving predicting outcomes for a hotel business, as a result of different Covid-19 scenarios. When not working Divya enjoys art, learning to drum and the NBA.

Bio: Throughout her career, Leila has worked in large creative agencies and niche data consultancies in Australia, the USA, and Europe. Her analytics experience covers a wide variety of clients including American Express, Vodafone, IBM, British Airways and Nestlé. As Head of Data Science and Analytics for Digitas UK, Leila is responsible for driving connected experiences powered by analytics and data science. To do this, her team combines methods that are tried and tested such as statistics, web, social and media analytics, data visualisation and data strategy with new techniques made possible with enhanced technology such as Machine and Deep Learning and Natural Language Processing.
Bio: Paramdeep is a Data Scientist at Digitas and has a special interest in NLP, having worked on a number of projects using text data and also having competed in NLP based data science competitions.