Data Analyst - Promotions

Job Description

Circle K (Part of Alimentation Couche-Tard group) is a global leader in the convenience store and fuel space, it has a footprint across 31 countries and territories. At the Circle K Business Centre in India, we are #OneTeam using the power of data analytics to drive our decisions and strengthen Circle K’s global capabilities. We make it easy for our customers all over the world – we partner with the business to empower the right decisions and deliver effectively, while rapidly unlocking value for our customers across the enterprise. Our team in India is an integral part of our talent ecosystem that helps advance us on our journey to becoming a data-centric company. The future of data analytics at Circle K is bright – and we’re only just getting started.

About The Role

The India Data & Analytics Global Capability Centre is an integral part of ACT’s Global Data & Analytics Team, and the Data Analyst will be a key player on this team that will help grow analytics globally at ACT. The hired candidate will partner with multiple departments, including Global Marketing, Merchandising, Global Technology, and Business Units.

The incumbent will be responsible for deploying analytics algorithms and tools on chosen tech stack for efficient and effective delivery. Responsibilities include delivering insights and targeted action plans, address specific areas of risk and opportunity, work cross-functionally with business and technology teams, and leverage the support of global teams for analysis and data.

Roles & Responsibilities

Analytics (Data & Insights)

• Clean and organize large datasets for analysis and visualization using statistical methods; verify and ensure accuracy, integrity, and consistency of data
• Identifying trends and patterns in data and using this information to drive business decisions
• Create the requirement artefacts e.g., Functional specification document, use cases, requirement traceability matrix, business test cases and process mapping documents, user stories for analytics projects
• Build highly impactful and intuitive dashboards that bring the underlying data to life through insights
• Generate ad-hoc analysis for leadership to deliver relevant, action-oriented, and innovative recommendations
  
  

• Improve data quality by using and improving tools to automatically detect issues
• Develop analytical solutions or dashboards using user-centric design techniques in alignment with ACT’s protocol
• Study industry/organization benchmarks and design/develop analytical solutions to monitor or improve business performance across retail, marketing, and other business areas
  
  

• Work with high-performing Functional Consultants, Data Engineers, and cross-functional teams to lead / support the complete lifecycle of visual analytical applications, from development of mock-ups and storyboards to complete production ready application
• Provide regular updates to stakeholders to simplify and clarify complex concepts, and communicate the output of work to business
• Create compelling documentation or artefacts that connects business to the solutions
• Coordinate internally to share key learning with other teams and lead to accelerated business performance
  
  

• Delivery Excellence
• Business disposition
• Social intelligence
• Innovation and agility
  
  

• Functional Analytics (Retail Analytics, Supply Chain Analytics, Marketing Analytics, Customer Analytics, etc.)
• Working understanding of Statistical modelling using Analytical tools (Python, PySpark, R, etc.)
• Enterprise reporting systems, relational (MySQL, Microsoft SQL Server, etc.), and non-relational (MongoDB, DynamoDB) database management systems
• Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)
• Cloud computing services in Azure/AWS/GCP for analytics
  
  

• Bachelor’s degree in computer science, Information Management or related technical fields
  
  

• 2 + years for Data Analyst
• Relevant working experience in a quantitative/applied analytics role
• Experience with programming and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Spark / SQL / Python