Senior Data Scientist - Banking

We're looking for a full-stack Data Scientist to support our Cards & Credit roadmap, partnering closely with Product, Engineering, Design, Underwriting, and Operations to shape how our card and credit products evolve and scale.

In this role, you'll apply strong analytical judgment and product intuition to help us understand customer behaviour, evaluate trade-offs, and make smart investment decisions across the cards and lending lifecycles , from eligibility and activation to spend, retention, incentives, and credit performance. You'll help build a data-informed culture across Mercury so teams can move quickly, measure what matters, and invest intelligently.

Key responsibilities include:

• Bringing impeccable communication and complete ownership , independently identifying opportunities, developing strong points of view, and influencing executives, Cards & Credit leaders, and cross-functional partners through clear, concise, and persuasive storytelling.
• Developing a nuanced understanding of cardholder behaviour and economics, helping teams reason about trade-offs between growth, engagement, risk, and unit economics.
• Defining, owning, and analysing metrics that inform both tactical decisions and long-term strategy across the cards and credit lifecycle (e.g., eligibility, activation, spend, utilisation, rewards, retention, loss signals).
• Designing and evaluating experiments using rigorous statistical approaches, including A/B testing, cohort analysis, causal inference techniques, and trend analysis.
• Building and improving data pipelines and tools to streamline data collection, processing, and analysis workflows, ensuring the integrity, reliability, and security of data assets.
• Building and deploying predictive models to forecast key outcomes, inform product treatments, and deepen understanding of causal drivers.

Requirements include:

• 7+ years of experience working with large datasets to drive product or business impact in data science or analytics roles.
• Fluency in SQL and comfort with Python.
• Strong judgment in defining and analysing product metrics, running experiments, and translating ambiguous questions into structured analyses.
• Exceptional proactivity and independence , identifying opportunities, forming strong points of view, and making your case to stakeholders.
• Experience with ETL processes and modern data modelling (e.g., dbt, dimensional models, Airflow), with a solid understanding of how data is produced and consumed.
• Experience in analytical approaches ranging from behavioural modelling to experimentation to optimisation , and, importantly, know when simpler approaches are the right answer.
• Apply AI tools to accelerate analytical and business workflows, improving scalability, decision quality, and reducing manual or repetitive work across teams.

Nice to have:

• Experience working on cards or credit products, with familiarity in card economics and lifecycle concepts (e.g., spend behaviour, interchange, rewards and incentives, utilisation, credit limits, retention).
• Experience developing quantitative pricing models or engines (e.g., dynamic pricing, incentive optimisation, or marketplace pricing systems).
• Experience applying optimisation techniques to resource allocation or decision systems (e.g., customer operations, capacity planning, or policy optimisation).
• Experience building or supporting credit models, including probability of default modelling, cashflow modelling, or dynamic credit limit setting.