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Director of Decision Science
full-time•London
About this role
<p> </p>
<p class="p1">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.</p>
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<p><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":0,"335559740":240}"> </span></p>
<p><strong><span data-contrast="auto">Who are you</span></strong><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":0,"335559740":240}"> </span></p>
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<p><span data-contrast="auto">You are a pragmatic leader who combines deep machine learning expertise with commercial credit instincts. You thrive in cross-functional settings, enjoy building high-performing teams, and take responsibility for models in production — from design through validation to monitoring and governance. You are energised by building model solutions that enable partners to deliver great customer experiences while protecting the business.</span><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":0,"335559740":240}"> </span></p>
<p><span data-ccp-props="{"201341983":0,"335551550":6,"335551620":6,"335559739":0,"335559740":240}"><span data-contrast="auto">This senior leadership role sits at an important inflection point for our product roadmap. You will lead the Decision Sciences function responsible for end-to-end credit model development, validation, and monitoring across a portfolio of B2B embedded-lending products which includes (</span><em><span data-contrast="auto">but not limited to</span></em><span data-contrast="auto">) flexible lines of credit, BCA and its variants.</span> </span></p>
<p><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></p>
<p><strong><span data-contrast="auto">What you’ll be doing</span></strong><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></p>
<ul>
<li><strong><span data-contrast="auto">Lead on model development and delivery: </span></strong><span data-contrast="auto">Own end-to-end model lifecycle for approval, scorecards, propensity, fraud, and collections models across seller and buyer products. Design features, run experiments, iterate on multi-bureau data pipelines, and productionize models by working closely with engineering teams.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Set modelling strategy and standards: </span></strong><span data-contrast="auto">Define modelling standards, validation playbooks, documentation requirements, and SLAs for model deployment and change control. Ensure compliance with regulatory and audit expectations for governance and explainability.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Build and scale model monitoring: </span></strong><span data-contrast="auto">Implement monitoring for model drift, population stability, performance degradation, and business impact. Create alerting and remediation workflows and own model refresh cadence.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Drive technical excellence: </span></strong><span data-contrast="auto">Champion advanced ML approaches which include (</span><em><span data-contrast="auto">but not limited to</span></em><span data-contrast="auto">) Gradient boosted decision trees, Survival or Hazard models and Bayesian models. Develop feature engineering and robust statistical techniques for driving SMB lending products. Balance complexity with interpretability and latency constraints.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Partner with product, data, and commercial teams: </span></strong><span data-contrast="auto">Translate model outputs into decisioning rules, pricing signals, and partner-level policies. Collaborate on experimentation, A/B testing, and propensity-to-convert vs risk trade-offs.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Lead, Coach, and Empower the team: </span></strong><span data-contrast="auto">Manage a team of 7+ data scientists and analysts including the Head of Decision Analytics. Recruit, mentor, and create clear career trajectories; run technical reviews, code and model clinics, and establish a continuous learning culture.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Communicate to stakeholders: </span></strong><span data-contrast="auto">Explain modelling choices, promote growth while managing risk trade-offs, and performance to executives, partners, and auditors through crisp written reports and presentations.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
</ul>
<p><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></p>
<p><strong><span data-contrast="auto">What we think you’ll need</span></strong><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></p>
<p> </p>
<ul>
<li><strong><span data-contrast="auto">Experience: </span></strong><span data-contrast="auto">Proven building credit or risk models in financial services with substantial recent experience in B2B unsecured lending for sellers/platforms or embedded-finance ecosystems.</span></li>
<li><strong><span data-contrast="auto">Technical depth: </span></strong><span data-contrast="auto">Proven hands-on experience developing production ML models using XGBoost, GBM, and related techniques. Strong Python and SQL skills for feature engineering, model training, and data validation. Experience with model deployment frameworks and MLOps practices.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Full model lifecycle expertise: </span></strong><span data-contrast="auto">Demonstrable experience in model design, feature engineering, OOT/OOS testing, validation, calibration, and governance. Familiarity with model explainability, regulatory expectations, and documentation for audit.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Product and portfolio thinking: </span></strong><span data-contrast="auto">Comfort with approval-rate vs loss-rate trade-offs, renewals economics, pricing impacts, and partner-level P&L. Experience translating model outputs into rules and pricing strategies.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Analytics and tooling: </span></strong><span data-contrast="auto">Strong data visualisation and analytics skills (Power BI, Tableau, or equivalent). Able to prototype quickly and collaborate with engineering to productionize models.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Judgment and communication: </span></strong><span data-contrast="auto">Track record making high-impact decisions on large exposures with clear rationales and reproducible audit trails. Excellent written and verbal communication with senior stakeholders.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">Leadership: </span></strong><span data-contrast="auto">Prior people management or function-lead experience with evidence of building standards, processes, and a culture of continuous improvement.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
</ul>
<p><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></p>
<p><span style="text-decoration: underline;"><span data-contrast="auto">Nice to have</span></span></p>
<ul>
<li><span data-contrast="auto">Prior experience with </span><strong><span data-contrast="auto">e-commerce or ISV partnership models</span></strong><span data-contrast="auto"> in the US and/or UK</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><span data-contrast="auto">Hands on experience with </span><strong><span data-contrast="auto">decision science libraries</span></strong><span data-contrast="auto"> such as scikit-learn, XGBoost/LightGBM/CatBoost, statsmodels; familiarity with SHAP/LIME for explainability.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><span data-contrast="auto">Exposure to </span><strong><span data-contrast="auto">commercial bureaus and third-party data vendors</span></strong><span data-contrast="auto"> (Experian, Equifax, D&B) and alternative data sources common in seller ecosystems.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><span data-contrast="auto">Working knowledge of </span><strong><span data-contrast="auto">Monitoring & quality tools</span></strong><span data-contrast="auto"> such as Evidently AI, WhyLabs, or equivalent for drift/PSI; Great Expectations for data tests.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><strong><span data-contrast="auto">General familiarity with ML platforms & MLOps:</span></strong><span data-contrast="auto"> AWS SageMaker (Studio, Pipelines), Databricks ML, MLflow, Feature Store, Docker/Kubernetes for serving, CI/CD (GitHub/GitLab), orchestration (Airflow/Prefect), and IaC where relevant.</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
<li><span data-contrast="auto">Working knowledge of implementing </span><strong><span data-contrast="auto">Agentic AI</span></strong><span data-contrast="auto"> solutions at scale</span><span data-ccp-props="{"201341983":0,"335559739":0,"335559740":240}"> </span></li>
</ul>
<p> </p>
<p><strong>What happens next?</strong><br><br></p>
<p>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!</p>
<p> </p>
<p><strong>Our hybrid approach</strong></p>
<p> </p>
<p>Working together in person helps us move faster, collaborate better, and build a great Liberis culture. Our hybrid working policy requires team members to be in the office at least 3 days a week, but ideally 4 days. At Liberis, we embrace flexibility as a core part of our culture, while also valuing the importance of the time our teams spend together in the office.</p>
<p> </p>
<p> #LI-CG1 </p>
What you'll do
- Lead the Decision Sciences function responsible for end-to-end credit model development, validation, and monitoring. Manage a team of data scientists and analysts while ensuring compliance with regulatory standards and driving technical excellence.
About Liberis
Liberis is an embedded finance partner for platforms, including vertical SaaS providers, marketplaces, payment processors, and payment companies. Liberis enables platforms to offer tailored financial solutions to their merchant ecosystems, supporting growth across businesses of all sizes.
Liberis partners closely with platforms, combining merchant data and distribution with over a decade of finance expertise and lending experience across economic cycles. By understanding merchant behaviour and business rhythm, Liberis embeds finance directly into platform workflows, delivering funding and financial tools at key moments in the merchant lifecycle.
Rather than offering standardised products, Liberis co-creates solutions around each partner’s brand, technology, and merchant needs. Its flexible, API-driven architecture allows platforms to configure, launch, and scale embedded finance offerings across 15 markets, with the ability to add new products over time without requiring further platform integration.
For platforms, Liberis delivers recurring revenue opportunities and supports merchant acquisition and retention. For merchants, Liberis provides fast and transparent access to capital, from $500 to $1M+, with clear pricing, flexible repayment aligned to business performance, and dedicated support.
Embedded Finance. Built Together.
Ready to join Liberis?
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Frequently Asked Questions
What does a Director of Decision Science do at Liberis?
As a Director of Decision Science at Liberis, you will: lead the Decision Sciences function responsible for end-to-end credit model development, validation, and monitoring. Manage a team of data scientists and analysts while ensuring compliance with regulatory standards and driving technical excellence..
Is the Director of Decision Science position at Liberis remote?
The Director of Decision Science position at Liberis is based in London, United Kingdom. Contact the company through Clera for specific work arrangement details.
How do I apply for the Director of Decision Science position at Liberis?
You can apply for the Director of Decision Science position at Liberisdirectly through Clera. Click the "Apply Now" button above to start your application. Clera's AI-powered platform will help match your profile with this opportunity and guide you through the application process.