Senior Data Analyst Jobs

Role Description

The Senior Analyst, Loyalty and Retail Analytics is responsible for analytics and insight that support all areas of business, ongoing enhancement and performance of a leading loyalty program and non-loyalty/operation analytics for a fuel’s retailer.

The ideal candidate has data analytics background, hands-on expertise in designing methodologies and advance analytic solution. The ideal candidate will also be an effective communicator with solid data mining capabilities preferably in a fast-moving retail like pharmacy, fuels retailing or grocery. experiences in predictive modeling, would be an asset.

This role is a unique opportunity to join a dynamic team of analytical professionals that partners up with Business and Technology to design innovative, value-adding customer engagement solutions for our clients. The role is a great fit for motivated individuals seeking to further develop their expertise in the area of retail, complex customer behaviour and predictive analytics.

Primary Responsibilities

• Lead communication with internal stakeholders and clients on projects
• Check data integrity and manipulate large volumes of data
• Prepare client facing presentations on analysis done and present those to the client or internal stakeholders
• Contribute to process standardization and creation of scalable solutions
• Contribute to the overall operations and culture of the company, fostering our values and policies
• Establish mechanisms for program / campaign performance measurement
• Create custom analysis that add strategic value to the understanding of customer behavior and / or campaign performance
• Generate analytical insights that drive the performance of a large scale loyalty program

Capability Requirements – education, skills & experience

• 4+ years of expert-level hands-on coding in SQL
• Attention to detail, high aptitude for problem solving and a natural interest in understanding and explaining consumer behavior / business
• 4+ years of experience within the field of data analytics
• A degree in Statistics, Mathematics, or other quantitative fields;
• Great at finding creative solution to analytical problems and data solutions.
• Excellent communication skills
• Solid understanding of the structure of relational databases
• Ability to develop analytical frameworks and generate / communicate business insights
• Good knowledge of SAS or Python is an advantage