EVENT - Tuesday
When6:00 PM - 7:30 PM
DSF Panel Series – Maximising your Data Science Team
Join us virtually for an interactive panel talk featuring leaders in data science. The panel will discuss how to maximise the performance of a data science team at both an individual and team level. We will hear four lightning talks from our speakers followed by the panel and chance to take open questions from the audience.
We aim to share, inspire & bring the data community together to build your industry network & have some exciting interactions with your fellow peers.
Ticket Allocation Process:
Registering here guarantees you a ticket for the Data Science Festival Event with our Panel on June 30th 2020. Once registered you will be sent your Zoom Link via email.
6:00 – Intro with David Loughlan – Founder of DSF and Data Idols
6:05 – Lightning talk 1 – Shorful Islam – Managing Teams remotely, on and off shore.
6:15 – Lightning talk 2 – Orestis Chrysafis – Let 1,000 flowers bloom: establishing, managing and growing a data science team for innovation.
6:25 – Lightning talk 3 – Aji Ghose – Focusing on Business Outcomes: Linking customer feedback with business metrics
6:35 – Lightning talk 4 – Bhagya Annapareddy – Why Data Engineering is critical for Data Science
6:45 – Expert Panel hosted by David – Maximising your Data Science Team
7:15 – Audience Q and A
7:30 – Close
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.