Top Data & Analytics Jobs

Generate actionable growth and financial insights through dataset curation, metric development, statistical modeling, and deep-dive analysis. Analyze company and regional growth drivers, customer segments and cohorts, and the financial impact of marketing and product initiatives. Build data visualizations and communicate findings to influence business decisions, while managing stakeholders and organizing work independently.

Own end-to-end regulatory reporting datasets across multiple jurisdictions, including regulatory data mapping, automated pipelines, visualizations, data quality controls, monitoring, and discrepancy resolution. Collaborate with finance, compliance, regulatory, product, and analytics teams to support licensing, audits, partnerships, and controlled growth. Use SQL, dbt, Snowflake, Airflow, visualization tools, and AI capabilities to deliver accurate, scalable reporting infrastructure.

Lead pricing analytics for Wise Platform by investigating cost data, improving data quality and allocation methodologies, monitoring financial performance, and identifying profitability and growth opportunities. The role requires building complex SQL data sources, developing reusable dbt models, explaining product economics, influencing pricing strategies, and partnering with analytics, engineering, and business teams.

Lead marketing analytics infrastructure that explains growth drivers, automates insight generation, and turns complex performance data into actionable narratives. Build and maintain analytical tools, including Lightdash reports, Streamlit apps, and AI-enabled automation. Identify opportunities in marketing financial processes, ensure data quality, develop growth frameworks, and partner with marketing, regional, product, and analytics teams to translate findings into strategic execution.

Investigate payment problems using SQL, Python, customer reports, and stakeholder input; identify root causes across payment flows; prioritize issues by impact; design practical solutions with Product, Engineering, Risk, Operations, and payment partners; lead actions through measurable outcomes; and improve investigation and measurement practices.

Lead product analytics for Wise Business: define and track KPIs/OKRs, build data logging and automated pipelines, run deep-dive analyses, quantify feature impact for prioritization, and translate findings into clear recommendations for product and leadership.

Build and optimize Lakehouse data pipelines (Trino + Iceberg) using Medallion Architecture to transform high-throughput event logs into audit-ready subledgers and reporting metrics. Implement stream processing with Kafka, embed automated reconciliation/data quality checks, collaborate with finance and product stakeholders, and mentor junior engineers.

Analyze card fraud disputes, trends, datasets, and prevention-rule performance to identify fraud patterns and reduce losses. Develop, test, optimize, and monitor fraud rules using data and machine-learning risk signals while balancing customer experience, approval rates, and costs. Investigate incidents and emerging attacks, support dashboards and KPIs, collaborate with Product, Engineering, Data Science, and Operations teams, and communicate recommendations to technical and non-technical stakeholders.

Partner with operations teams to drive analytics for capacity planning, forecasting, predictive modelling, and KPI implementation. Own data pipelines, provide operational health and cost analyses for KYC/FinCrime, track initiative performance, standardise processes, and deliver actionable insights using SQL, Snowflake, and visualization tools.

Build scalable People Analytics products and data infrastructure, partner with People stakeholders to solve business questions, embed analytic measurement into projects, work with APIs and complex datasets, create self-serve dashboards, and upskill the People tribe to drive data-informed decisions.