Lead Data Analyst

• Relevant Bachelor’s degree
  

Language(s): 

• English
  
• French, Portuguese, or Swahili is a plus
  

Technology:

• Data visualization and reporting in Tableau, PowerBI, Jupyter notebooks
  
• Code and ETL in Python and R
  
• AWS tools for data storage: RDS, Redshift, S3
  
• Statistical analysis in R or python (scipy, stats, etc)
  
• Sprints and Scrums in JIRA
  
• 5+ years of relevant experience
  
• Strong SQL, comfortable writing queries, data processing scripts, and understanding data structures
  
• Strong background in data visualization, preferably either Tableau, PowerBI
  
• Keen eye for detail and thoughtful investigation of data before relying upon it
  
• Demonstrated expertise in strategic analysis to impact decisions
  
• Excellent communicator, able to work with analysts from several different cultures and backgrounds, as well as senior leaders within the organization
  
• Willing to spend time in the field, to better understand how data are collected, as well as potential improvements to applications and tools to minimize threats to data integrity
  
• Sense of adventure and willingness to dive in, think big, and execute with a team
  

• Work with data and business intelligence analysts and strategists across nine countries and the global team to build dashboards and global reports to provide actionable insights, from leadership to the team on the ground.
  
• Provide training and support to analysts to understand the nuances of the data lake, build dashboards, and take advantage of existing reports and visualizations when appropriate.
  
• Work as a liaison with analysts to guide the data team in responding to their needs and requirements.
  
• Work with data team to design and update data storage (ex. table design) to facilitate readability, performance, and reliability of queries and reporting pipelines.
  
• Provide training and up-skilling on technical topics, such as simple to advanced SQL querying techniques, to 50+ analysts and data users in our markets.
  
• Work with data team to coordinate and prioritize business requests, based on real-world impact.
  
• Be willing to get your hands dirty in taking deep-dives into various data sources to investigate data integrity issues and sources of discrepancies.