ROLES AND RESPONSIBILITIES:

• Wrangles large amounts of data from multiple sources
  
• Cleanses and prepares data for modeling and analysis
  
• Uses the correct data mining approach to solve business problems including customer segmentation, marketing and promotional campaigns, operations enablers, and various market-growth initiatives
  
• Appropriately evaluates model results and iterates as necessary
  
• Consults on internal database(s) in collaboration with business partners (e.g., IT, Marketing) to ensure data quality
  
• Efficiently and accurately produces data reports, visualizations, and insights to meet the needs of business partners
  

REQUIRED TECHNICAL SKILLS:

• Minimum of 2+ years\' experience using data mining tools and advanced analytical methods in a business environment or advanced technical degree
  
• Proficiency with relational database systems
  
• Proficiency and proven experience with techniques in accurately joining large data sets from multiple sources and manipulating data to desired format
  
• Experience with data visualization
  
• Strong analytical and problem solving skills with a solid understanding of business
  
• Experience in one or more statistical programming languages (R, Python, SAS, SPSS)
  

REQUIRED EDUCATION:

Bachelor\'s degree in Economics, Statistics, Applied Mathematics, Computer Science, Management Information Systems or a related field

OTHER KEY QUALIFICATIONS:

• Demonstrated ability and proven results exemplifying initiative, project management skills, and accuracy/detail-orientation
  
• Ability to work independently and with team
  
• Extremely curious about data
  
• Strong organizational and prioritization skills
  
• Strong written and verbal communication skills
  
• Strong desire to learn new data mining languages and techniques
  

PREFERRED SKILLS AND EXPERIENCE:

• Knowledge and proficiency in R
  
• Master\'s degree
  
• Brings unique knowledge or expertise to team in some aspect of advanced analytics (e.g.; statistics, uplift modeling, marketing mix models, econometric modeling, predictive modeling, machine learning, etc.)
  
• Demonstrated ability to summarize and present complex analytics to senior leadership