Senior Data Scientist - Full Stack

<p><strong>Senior Data Scientist - Full Stack</strong></p> <p><span style="text-decoration: underline;"><em>Please note visa sponsorship is not currently available for this position. </em></span></p> <p>We are looking for a Senior Full Stack Data Scientist to join our Data & Analytics team at ClearScore. Data Scientists play a key role in our business, driving strategy and decision-making at all levels, which ultimately benefits our users, partners, and other teams across the organisation. We are seeking a proactive, outcomes-oriented individual, ready to take on broad ownership of a range of initiatives, to join our growing Global Targeting team. Working to enhance the ClearScore user experience through improved dynamic content targeting and prioritisation, you will take end-to-end ownership of data science and machine learning solutions across a variety of use cases, business areas, and markets. You’ll bring the knowledge and expertise required to evaluate transformative new approaches in machine learning and AI against our current implementations, applying your judgement and craft to incorporate these where they can add real value. Your contributions will directly support the Global Targeting mission, enabling the organisation to realise its overall strategy and goals.</p> <p>ClearScore is both a free credit score and report service and the UK's leading consumer credit marketplace. ClearScore has an amazing analytical community which includes Data Analysts, Scientists and Engineers. The community works collaboratively, sharing knowledge, tools, and best practice, to ensure a landscape in which team members can develop their full potential and deliver maximum positive business impact.</p> <p><strong>What you’ll be doing</strong></p> <ul> <li>Leading the end-to-end development of data science and machine learning solutions - from business concept through to impact evaluation - to enable a better user experience through data-driven Targeting</li> <li>Working closely with cross-functional stakeholders to shape how Data Science and the broader Targeting initiative can effectively support business needs to drive maximum impact</li> <li>Keeping our modelling practice at the cutting-edge: building a deep understanding of new developments in ML and AI, like Foundation Models, testing these rigorously against our production systems, and leading our adoption of those that prove their value to drive better outcomes for our users and business</li> <li>Helping to set the quality bar for what we put into production: scrutinising data, features and model behaviour, and surfacing problems in our data and processes before they reach our users</li> <li>Identifying and implementing improvements and optimisations in our model development and management processes, driving more efficient and standardised ways of working, leading by example in what you deliver</li> <li>Driving the strategic utilisation of model outputs for decision making, working with the Global Targeting squad to use model outputs to change what users see</li> </ul> <p><strong>What you’ll need to succeed in the role</strong></p> <ul> <li>A self-starter mindset: curious, collaborative, and committed to continuous learning - including the adoption of new tools as they emerge. You stay abreast of advances in ML and AI, demonstrating the judgement required to assess when newer techniques will outperform conventional ones and when they won’t</li> <li>A desire to deeply understand a problem and its importance to the business before attempting to solve it, and being comfortable proactively seeking that context rather than waiting for it</li> <li>A strong ability to think critically about, and reason concisely with, data. A drive to understand our users, products, and how users interact with them, and to build an advanced knowledge of our data assets and how these connect to our users’ financial wellbeing through the product experience</li> <li>Advanced Python and SQL skills, and a strong understanding of dbt and Analytics Engineering for feature engineering. In-depth knowledge of varied statistical and machine learning techniques. You're capable across the full model lifecycle, including how models get deployed and maintained effectively in a production environment</li> <li>Demonstrable experience of using business-domain knowledge to drive model development or derive insights from data</li> <li>The ability to explain the key findings from complex analysis and modelling exercises to both technical and non-technical audiences. You feel at home interacting with stakeholders from across different specialisms around the organisation</li> </ul> <p&