Dan Kellett, Chief Data Officer, Capital One UK
Describe your career to date
I studied Mathematics and Statistics at the University of Nottingham, joined Capital One as a graduate statistician in 2000 and have been here ever since. My initial projects were building and maintaining statistical models for marketing direct mail, but over the following five years I worked on models and analysis across the whole customer lifecycle, from marketing through new customer acquisition and existing customer management.
After managing teams of statisticians across multiple European countries, I took on overall leadership for the UK statistical team in 2012 as Director of Statistics. In this role I was responsible for team strategy, delivery, recruitment, and development; this included a job family transition to bring in a greater breadth of data science skills.
Almost four years ago I moved into the UK Chief Data Officer role. By leading all aspects of data, we have benefitted from the ability to focus on what really matters and breaking down silos. This year has seen the delivery of a large-scale cloud data transformation delivered to budget and on time. This has revolutionised our ability to rapidly access high quality data, leading to a step change in the amount and quality of insight.
A large part of my role is bringing the outside-in, whether that is through new data sources, new innovations for analysis, or influencing the direction of the industry. One of the highlights of my career was my involvement in the FCA and Bank of England Artificial Intelligence Public and Private Forum, helping to shape how AI can be used and managed responsibly in financial services.
Data literacy is a key enabler of the value and impact from data. How are you approaching this within your organisation?
A key personal objective for me this year was the challenge of boosting the data and numeracy skills of every Capital One employee: I believe this is essential to building highly effective, diverse teams. Central to this goal was closely aligning with our CEO to harness her sponsorship and passion.
Rather than relying on existing data science career pathways, we have encouraged a new internal scheme to make data roles available to talented individuals from across the business, regardless of their background, gender, or qualifications. This removes the barriers to progression, particularly those which disproportionately impact certain socio-economic groups.
The centrepiece of our wider initiative is offering level three data literacy apprenticeships to over 50 employees. This required a large degree of influence with all leadership team members to get their buy-in. We partnered with Multiverse to ensure high quality learning and support and launched in September with apprentices from all 13 departments in the UK organisation; from legal to marketing, operations to risk.
Additionally, we organise lunch-and-learn sessions of key data topics such as an introduction to statistics, Excel basics, and credit card economics. These sessions are taught by in-house experts and are available to everyone.
This broader push on skills has seen more employees aware of the key data we capture about our customers, and on our business performance. This has led to better quality decision making and a more diverse set of opinions.
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