Optimisation Data Analyst
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Summary
Analyze payment datasets to spot trends, build analytics pipelines, and deliver optimization recommendations for merchants using Python, SQL, and PySpark.
You will analyze large-scale payment datasets, identify performance trends and optimization opportunities, deliver recommendations to customers, and drive scalable improvements. You will build analytics solutions, automation pipelines, and self-service tools, lead experiments, collaborate with product and commercial stakeholders, communicate insights, and support analytical best practices.
Responsibilities
- Analyze large-scale payment datasets to identify performance trends and optimization opportunities
- Deliver recommendations to customers and drive scalable opportunities across the merchant base
- Design and build scalable analytics solutions automation pipelines and self-service tools
- Partner with Product Data and Commercial teams to develop analytical solutions
- Lead A/B tests and data investigations
- Synthesize complex data into narratives for technical and non-technical audiences
- Support knowledge-sharing and analytical best practices
Requirements
- 3–5 years of relevant experience in data analytics data science or a similar role
- Python
- SQL
- PySpark
- Large-scale data processing
- ETL and data pipelines
- Data validation
- Spark
- Airflow
- Git
- Looker or Tableau
- Dashboard development
- Statistics
- Hypothesis testing
- Data mining
- Cross-functional collaboration
- Stakeholder management
- Communication
- Data storytelling