Shorful Islam – Managing Teams remotely, on and off shore.
Orestis Chrysafis – Let 1,000 flowers bloom: establishing, managing and growing a data science team for innovation.
Aji Ghose – Focusing on Business Outcomes: Linking customer feedback with business metrics
Bhagya Annapareddy – Why Data Engineering is critical for Data Science
Shorful Islam – Chief Product and Data Officer at OutThink
Talk Summary: I will discuss my experience of setting up and managing remote data and analytic teams both on and off shore
Orestis Chrysafis – Senior Manager, Research & Development at HSBC
Talk Summary: This lightning talk will immerse itself in the factors that affect the daily dynamics of a professional data science team that holds a brief for continuous innovation. Talent acquisition, structure, skillsets, knowlegde management and the interplay between individual intellect and the hive mind.
Aji Ghose – VP of Data & Research at Chattermill
Talk Summary:Customer experience professionals spanning insight, market research and strategy roles all want to gain an in-depth understanding of customer perceptions and behaviours in order to turn data into actionable business recommendations. Yet, many are still not engaged in large-scale and data-driven analysis of their customer feedback data. Moreover, linking this to actual customer behaviours is rarely explored. Here we present Chattermill’s approach to large-scale analysis of customer feedback and connecting this to both soft and hard commercial metrics.
Bhagya Annapareddy – Principal Data Engineer at QuantumBlack, a Mckinsey Company
Talk Summary: Data scientists spend 80% of their time cleaning data rather than creating insights. Data scientists only spend 20% of their time creating insights, the rest wrangling data. It’s frequently used to highlight the need to address a number of issues around data quality, standards à access for all of this to be addresses and the solution for this is having data engineers for data science projects.