Responsibilities

• Develop, build, and measure performance on operational metrics (e.g., productivity, service level agreement, quality, cost, efficiency, timeliness) and generate insights to improve the efficiency of operations.
• Learn complex technical concepts and systems, and deliver meaningful results using them. Communicate technical results and methods clearly.
  
• Partner with Data Science and Strategy teams to prioritize and execute quantitative analyses and advanced modeling that deliver actionable insights.
  
• Analyze processes to identify opportunities for improvement, define requirements, and collaborate cross-functionally and globally to improve processes and tools.
  
• Analyze and debug escalations and identify trends that can indicate bigger product risks.
  
  
  

Minimum qualifications:

• Bachelor's degree in Engineering, Math, Quantitative Science, or related technical field, or equivalent practical experience.
  
• 1 year of experience in statistical problem solving and analyzing data sets using SQL or comparable coding language (e.g., Python, R, Java, C++).
  
• 1 year of experience working in data analytics, consulting, data science, engineering, or a technical operations role.
  

Preferred qualifications:

• 4 years of experience in an investigative role.
  
• Experience in extracting, sampling and visualization of large data sets, writing and maintaining ETLs which operate on a variety of structured and unstructured sources, delivering production level metrics, insights and actions.
  
• Experience in project management and process optimization with data analytics.
  
• Knowledge of abuse prevention, policy and regulatory systems.
  
• Ability to take ownership of projects by setting and achieving milestones, synthesizing input from many stakeholders, managing multiple projects simultaneously, creating outputs appropriate to the audiences and driving final deliverables.
  
• Excellent written and verbal communication skills.