Senior Credit & Commercial Strategy Analyst

01Some key info for you

🌱 We were founded in 2007

💰 We have provided over $3bn of funding to small businesses so far

🚀 We have been named in CNBC & Statista Top 150 UK Fintechs for 2025

🌍 We're a global team, with a dynamic presence in 6 key locations around the world

🧠 We're a thriving community of over 290 innovative minds

👩🏾 🤝 👨🏼 We're a vibrant melting pot, celebrating over 27 nationalities in our team

🏢 Our team brings experience from over 740 previous companies, from startups to global giants

🎯 We have just been named as one of FinTech’s Finest 50 by Welcome to the Jungle

💪 We’re proud to be an accredited Real Living Wage employer, ensuring everyone is paid fairly for the great work t

02The team

We are the Credit and Commercial Strategy team with a goal to drive intelligent decision-making and pricing strategy by applying advanced statistical analytics to a wealth of data. At the heart of the Risk function, our focus is to deliver high-quality instant decisions and pricing strategies for our customers around the world.

Risk team is a global team covering Portfolio Analytics, Credit and Commercial Strategy, Underwriting and Collections. We're on a mission to grow Liberis into the world's leading embedded business finance provider, and we're looking for a Senior Credit & Commercial Strategy Analyst to help us make that happen!

03The role

You'll design world-class decisioning and pricing strategies that deliver value to both our customers and Liberis. This is your chance to work on diverse projects that aim to fund as many customers as possible while staying within our risk appetite and to help us achieving our ambitious commercial goals.

We're looking for someone with experience in an analytical role who can use data to solve business problems, influence decision-making, and deliver meaningful commercial insights.

04What you’ll get to do

• Shape lending decisions: Analyse application data and portfolio performance to recommend changes to eligibility, acquisition, pricing and credit decisioning strategies.
• Develop and test strategies: Design and evaluate credit and pricing policies that help us fund more businesses while managing risk and supporting profitable growth.

• Monitor performance: Own and improve monitoring of decisioning rules, model performance and portfolio outcomes, including as new products and partners launch. Investigate changes and recommend action.

• Make better use of data: explore new and existing data sources; work with predictive models to improve lending decisions, propose features with our Machine Learning team, and contribute to model validation and governance.
• Turn analysis into action: Build clear proposals, explain assumptions and trade-offs, and present recommendations to senior risk and business leaders.
• Work across the business: Represent Risk and partner with Risk, Product, Commercial, Technology and partnership to put strategies into practice and assess their impact

05The interview process

• Screening call with the Talent Team (30 mins)
• Video interview with the Hiring Manager (45 mins)
• Task based interview (1 hour)
• Interview with the wider Risk Team (30 mins)

06What we think you’ll need

• Hands-on analytical experience, with examples of projects you've owned and recommendations that have informed business decisions.
• Strong SQL and Excel skills, with the ability to investigate data, check its reliability and turn findings into practical recommendations.
• Experience in one or more relevant areas, such as lending risk management, credit decisioning, acquisition strategy, pricing, commercial analytics or applied data science.
• Sound judgement when weighing commercial opportunities against potential risks, with a willingness to challenge assumptions.
• The ability to explain complex findings clearly and adapt your communication to different audiences.
• A proactive, autonomous approach, with attention to detail and the confidence to ask for support when needed.
• An appetite to understand how machine learning models are developed.
• Python, GCP and experience with visualisation tools such as Looker, Power BI or Tableau would be helpful, as would exposure to predictive model development, validation or monitoring.

07What happens next?

Next steps If this opportunity feels like the right fit for your next career move, we’d love to hear from you!

Even if you don’t meet every requirement, don’t hesitate to apply or reach out to Chess (Internal Recruiter) on

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