Liberis

Senior Credit & Commercial Strategy Analyst

London, United Kingdom · Work style not stated

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About the role

Description from the employer’s posting. Check the employer’s page for the current version.

  • EmployerLiberis
  • LocationLondon, United Kingdom
  • Work styleWork style not stated
  • Employer posted

Please note that Liberis is unable to provide visa sponsorship for this position. Therefore, all candidates must have full rights to work in the UK for a minimum of 2 years.

At Liberis, our mission is to empower small and medium-sized businesses by removing finance as a friction to growth, delivering contextual, embedded financial solutions to support merchants at every stage of their business lifecycle.

The 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!

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The 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.

What you’ll be doing

  • Lead the development and optimisation of global decisioning strategies
  • Shape pricing strategy that balances risk, commercial value and customer outcomes
  • Make a meaningful impact to the business by driving positive outcomes for as many customers as possible
  • Explore new and current data sources to optimise decisioning and pricing policy
  • Collaborate with key risk stakeholders to maintain an acceptable risk level in a fast-evolving environment
  • Represent Risk to wider business; collaborating with Product and Commercial teams to unlock business value
  • Work closely with the Machine Learning team on the life cycle of predictive model; propose features for future development
  • Own and continue to improve the monitoring capability for auto-decisioning rules and predictive models

What we think you’ll need

  • 2-4 years of experience in an analytical role
  • A strong analytical mindset with a passion for turning complex data into insights
  • The ability to communicate your findings clearly and effectively
  • A proactive approach to driving initiatives in a dynamic environment
  • A keen eye for detail without losing sight of the bigger picture
  • Confidence to work autonomously, while knowing when to seek support
  • An appetite to understand machine learning models and how they are developed
  • Proficiency in SQL is required
  • Strong MS Excel skills are required
  • GCP experience and Python skills are a plus
  • Experience with data visualization tool such as PowerBI, Looker.
  • A solid STEM background is great, but we care more about aptitude than formal education

What happens next?

Think this sounds like the right next move for you? Or if you’re not completely confident that you fit our exact criteria, apply anyway and we can arrange a call to see if the role is fit for you. Humility is a wonderful thing, and we are interested in hearing about what you can add to Liberis!

#LI-CG1

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At a glance

  • SenioritySenior
  • Employer posted
  • Added to ROLIVA
  • Last checked

Skills in this posting

Skills ROLIVA found in the employer’s own description above. A mention is not a requirement.

SQL Python Excel Looker GCP Machine learning

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