Data Insights Analyst at Global Payments

Mexico City, Mexico City, Mexico

Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Payments, FintechIndustries

Bachelor’s Degree in Data Analytics, Statistics, Computer Science or a related field (Master’s degree preferred)
2 years of relevant experience as a data analyst, preferably in payments, fintech or financial services
Strong SQL skills and data manipulation
Experience with BI/visualization tools (e.g. Microstrategy, Power BI, Looker)
Effective communication and data storytelling skills
Professional experience working with large datasets from various sources and interpreting the data to meet business needs
Comfort working in fast-paced, cross functional environments
Analytical and Critical Thinking - interpret complex data, identify problems and develop solutions
Communication - clearly present findings and insights for technical and non-technical audiences
Curiosity and Problem Solving - use data to solve specific business problems, with intellectual curiosity to uncover root causes and identify new opportunities
Technical Proficiency - SQL, Microsoft Office Suite, Microstrategy, Looker
Language Proficiency - Fluent in English (written and spoken)

Understand requestors' requirements, develop data collection systems, maintain databases
Interpret results using statistical techniques, create reports and visualizations (such as dashboards)
Collaborate with teams to inform strategic decision-making
Interpret a requester's data needs and translate these needs into proper data requirements
Gather and analyze transactional and customer data from multiple sources, map and translate that data into meaningful insights
Combine and clean datasets to ensure accuracy and consistency ready for analysis
Analyze the data by applying statistical techniques and tools to identify trends, patterns and correlations within the data
Communicate complex quantitative analysis in a clear, precise and actionable manner
Create reports, dashboards or other forms to present findings in a visual manner that stakeholders can understand and digest
Identify, define and bring to market complex data science projects with high business impact across cross functional teams