View the Latest Edition of Data Insight Leaders

View All Speakers

Dan Kellett

Director of Data Science
Capital One

As head of the Data Science at Capital One UK, Dan leads an 18-strong cross-functional team that is changing the way we do business. He uses the latest distributed computing technologies and operate across many billions of customer transactions. The models and data products that his team builds, unlocks big opportunities for the business and help UK consumers save money and reduce friction in their financial lives. He and his team have recently implemented a new open source analytic environment for model building/deployment as well as a sandpit for testing new analytic approaches. The last 6 months have seen the launch of major new credit risk models, leveraging the latest machine learning approaches to optimise our decisions. He has also made recent strides in understanding and mining customer contact data to better meet their needs and help them succeed. Dan have over 15 years of experience in analytics within the Finance industry. He has looked to build and lead highly-skilled, engaged teams focused on using data to solve real business problems.

Check out the incredible speaker line-up to see who will be joining Dan.

Download The Latest Agenda

Day 2 - Setting Your Division Up For Future Success

Wednesday, January 4th, 2017

09:20 Oxford Style Debate: Establishing an optimum operating model-Should data analytics teams be centralised or decentralised in an organisation to reap their full potential?

Should data analytics be centralised or decentralised to reap optimum business benefits?
Does the output of independent centralised data functions differ from those that sit within the business?
Lowering corporate restrictions: Does a centralised data function really have less corporate restrictions or do they face the same level of push back?
Will having your data function at the top of the company hierarchy put you in a better place to create a holistic overview of business needs, or will you still face the same silo mentality challenges?

15:15 Case Study: Training right-How to implement internal training programmes that equip your staff with the varied data science skill sets currently absent in the workplace

Data science boot camp: What is the best approach for incorporating in-house training programmes for current employees?
How do you best scan your current data skill base to identify gaps and increase team capabilities?
Building a data science curriculum: How do you best train for hard and soft skill requirements to fit the unicorn bill?
Sourcing internal talent: How do you successfully identify who is ready for a new skill set progression plan?
Making an impact: How to do ensure new recruits truly add a new dimension to the team?