Senior Business Intelligence Engineer - 100% Remote Opportunity!
Help Kohl's become the most sophisticated pricing operation in retail by leveraging your advanced data and analytical skills to identify opportunities and inform the roadmap in the pricing technology domain!
Responsible For:

• Work as part of a balanced team, including product management, engineering and design
• Collaborate with cross functional teams to identify problem statements and areas for analysis prior to any experiments or testing
• Independently perform analysis of complex data sources to determine value and use given the specific problem statement
• Acquire and compile structured and unstructured data from disparate sources and verifies its quality, accuracy and reasonableness
• Independently reviews, prepares, designs and integrates complex (type, quality, volume) data correcting problems and recommends data cleansing/quality solutions to major issues

• Develop and apply complex data derivations, business transformation rules, and data requirements
• Perform analyses of historical data to surface trends and insights using advanced analytical methods and present findings to stakeholders
• Creates data visualizations to help support data exploration & translate analytic insights into tangible, actionable solutions
• Strong business acumen and deep desire to leverage data to inform company strategic and tactical decisions
• Document new and existing models, solutions, and implementations
• Actively seeks opportunities to expand technical knowledge and capabilities
• Ability to synthesize and present complex data insights and concepts to business leaders

The Ideal Candidate will have:

• Undergraduate degree (BA/BS) in an analytic/quantitative field. Master's degree preferred.
• A minimum of 3+ years of relevant professional experience in a data analysis role
• Experience using data warehouses including Teradata & Google Big Query
• Advanced SQL capabilities + experience querying data with MY SQL
• A minimum of 1+ years of relevant experience with retail pricing (preferred)
• Programming with Python and R (preferred)