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Leads strategically important data science initiatives across complex business domains. Shapes data strategy, develops measurement frameworks, applies experimentation, causal inference, forecasting, optimization, and decision science, and partners with senior leaders to drive measurable outcomes. Remains hands-on with complex analyses, experiments, models, and prototypes while establishing technical standards, governance, reproducibility, and documentation. Coaches data scientists and analytics engineers and stewards critical data products end to end.

Analyze user behavior and product performance through quantitative analysis, data mining, reporting, and large-scale A/B experimentation. Partner with product, engineering, marketing, and finance teams to guide decision-making, measure key outcomes, understand customer lifetime value, assess product profitability, and improve data collection. The role is embedded within cross-functional product squads and contributes to product strategy and user engagement.

Lead product-focused data science work: run quantitative analyses and large-scale A/B tests, enable product teams with measurement, drive lifetime value analysis with finance, and partner with engineers to ensure correct data collection and actionable insights.

Provides second-line oversight of consumer and small-business credit risk across lending products. Analyzes portfolio performance, develops monitoring metrics, challenges credit strategies, leads thematic assurance reviews, collaborates on model validation, supports stress testing and forecasting, and maintains the Credit Risk Framework. Partners with first-line teams on product launches and strategy changes while communicating risk insights to stakeholders and committees.

Data science intern working on real customer projects involving data wrangling, analysis, predictive modeling, visualization, and product insights. The role uses Python, SQL, Looker, and spreadsheets to transform raw data into customer stories and support data-driven product decisions. Interns collaborate with Data teams, learn commercial and product analytics, and complete a full-time 12-week hybrid internship in London.

Software engineering interns will design, write, test, review, and ship code supporting customer features. They will collaborate with product managers, designers, data analysts, and experienced engineers while learning new technologies and engineering practices. Interns will work on a real customer project, receive mentorship, seek feedback, and contribute to Monzo’s banking platform during a minimum 12-week summer internship.

Manage and optimize savings product pricing by analyzing portfolio performance, pricing elasticity, deposit trends, customer behavior, competitor rates, and macroeconomic conditions. Model volume, margin, and profitability trade-offs; forecast deposits; develop pricing datasets and Looker dashboards; and recommend strategic decisions. Partner with Finance, Treasury, Data Science, and Product teams to translate complex financial analysis into actionable growth and pricing decisions.

Manages credit reference agency and external-data supplier relationships across consumer and commercial lending. Responsibilities include supplier onboarding, contract and product tracking, spend reconciliation, budget optimization, cross-functional coordination with Legal, Security, Data Protection, and Procurement, product testing, EU workstreams, and procurement lifecycle activities.

Oversee outsourced FinCrime operations partners, monitor performance and metrics, and drive remediation across screening, onboarding, transaction monitoring, AML/CTF, and fraud controls. Partner with product, technology, data science, engineering, compliance, audit, and vendors to implement automated solutions, manage change priorities, support assurance activities, and prepare governance materials. Lead cross-functional initiatives supporting EU expansion and mitigate financial crime and money laundering risks across banking products.

Oversee outsourced fraud and dispute operations partners, monitor performance and fraud metrics, drive data-informed mitigation strategies, and coordinate change implementation. Collaborate with product, technology, data science, engineering, compliance, audit, and third-party vendors to address fraud trends, chargebacks, assurance actions, and EU expansion challenges. Support governance reporting, committee materials, prioritization, and automated fraud-monitoring solutions.