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About the Role
Yonder is seeking a Senior Data Scientist to develop predictive models crucial for key business decisions across credit acquisition, portfolio management, collections, fraud, and rewards. This hands-on role involves working directly with decision-makers to build, validate, implement, and monitor models that improve business outcomes.
Responsibilities
- Develop and continuously improve acquisition models to assess applicant risk, affordability, and customer value using various data sources.
- Build behavioral models for portfolio management to predict member behavior and enhance credit profitability.
- Create models to identify member responses to interventions, optimizing collections strategies.
- Collaborate with Fraud and Financial Crime teams to build better fraud detection models.
- Utilize machine learning to improve rewards by leveraging member data for timely and relevant offers.
- Own the end-to-end modeling lifecycle, from hypothesis to production implementation and monitoring.
- Identify and integrate new data sources to enhance model prediction capabilities.
- Establish robust model monitoring and validation processes to track performance post-deployment.
- Translate complex modeling outputs into clear, simple explanations for non-technical stakeholders.
- Contribute to establishing data science standards, tooling, and development practices at Yonder.
Requirements
- Proven experience building predictive models that have been successfully deployed into production and improved business outcomes (risk, revenue, customer experience, or operations).
- High proficiency in Python and SQL.
- Comfort working directly with large, messy datasets.
- Deep understanding of predictive modeling techniques, including logistic regression and gradient boosting.
- Ability to select appropriate algorithms based on problem statements.
- Proficiency in model evaluation, considering metrics beyond headline accuracy, such as calibration, stability, and drift.
- Strong commercial acumen, understanding the business impact of model choices.
- Ability to operate with ambiguity and define solutions for loosely defined problems.
- Willingness to own work end-to-end, including implementation, monitoring, and adjustments.
- Excellent communication skills, able to explain technical concepts to non-technical audiences.
- Experience in consumer lending, credit cards, fraud, or fintech is valuable.
- Experience with bureau data, behavioral credit models, collections models, transaction data, fraud detection, or customer recommendation systems is a plus.
- A builder's instinct, focused on rapid deployment and iteration of models.
- Willingness to be in the office at least three days a week.
Skills
- Predictive modeling
- Python
- SQL
- Feature engineering
- Model development
- Model validation
- Model implementation
- Model monitoring
- Data exploration
- Logistic regression
- Gradient boosting
- Machine learning
- Risk assessment
- Fraud detection
- Credit scoring
- Data analysis
- Communication
Location
- London Shoreditch
Work Type
- Office-first
- Remote-friendly
- Hybrid
Experience Level
- Senior
Salary/Compensations
- £94,589 - £111,502
Benefits
- Stock options (£80,479 - £105,003)
- 35 holidays (27 days annual leave + 8 days public leave)
- Team-building offsite
- Private healthcare with Bupa
- Up to 12 weeks enhanced parental leave
- Learning & training allowance (£750/year)
- Regular team breakfasts and lunch
- Regular team events
- Cycle-to-work scheme
- Fresh pour-over coffee
About the Company
- Yonder is a credit/debit rewards card company focused on fairness, flexibility, and user enjoyment, offering rewards on everyday purchases for travel, dining, entertainment, and more.
- Our mission is to empower people to build financially rewarding lives.
- We have built an award-winning rewards card that allows members to earn points for experiences worldwide with no FX fees.
Equal Opportunity
- We know that diverse teams build better products. If you’re from an under-represented community, we’d especially love to hear from you.
- Even if you don’t feel 100% qualified, please do apply anyway. Your attitude and desire to grow are just as important as your experience.