Data Scientist

Job Description

Circle K (Part of Alimentation Couche-Tard Inc., (ACT)) is a global Fortune 200 company. A leader in the convenience store and fuel space, it has a footprint across 31 countries and territories. Circle K India Data & Analytics team is an integral part of ACT’s Global Data & Analytics Team, and the Data Scientist will be a key player on this team that will help grow analytics globally at ACT. This is a unique opportunity to be a part of an experienced team of data scientists and analysts within a large organization.

The Data Scientist is responsible for delivering advanced analytics and insights that drive business results and operational excellence to our dynamic and forward-thinking Merchandise team in Europe. The ideal candidate should possess both technical capabilities as well as commercial savviness, should be able to drive independent analysis as well as work effectively in a group.

About The Role

We are looking for an individual who is a proven problem solver with exceptional critical thinking ability. The candidate should have a high sense of curiosity and be comfortable with ambiguity when faced with a difficult challenge. Additionally, the candidate should possess excellent communication skills, the ability to collaborate with others, and simply and effectively communicate complex concepts with a non-technical audience.

Roles & Responsibilities

Analytics (Data & Insights)

• Evaluate performance of categories and activities, using proven and advanced analytical methods
• Support stakeholders with actionable insights based on transactional, financial or customer data on an ongoing basis
• Oversee the design and measurement of experiments and pilots
• Initiate and conduct advanced analytics projects such as clustering, forecasting, causal impact
• Build highly impactful and intuitive dashboards that bring the underlying data to life through insights
  
  

Operational Excellence

• 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
  
  

Stakeholder Management

• Work with Peers, Functional Consultants, Data Engineers, and cross-functional teams to lead / support the complete lifecycle of 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
• Be an advocate for a data-driven culture among the stakeholders
  
  

Job Requirements

Education

• A higher degree in an analytical discipline like Finance, Mathematics, Statistics, Engineering, or similar
  
  

Relevant Experience

• Experience: 3-4 years for Data Scientist
• 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
• Excellent communication skills in English, both verbal and written
  
  

Behavioural Skills

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

Knowledge

• Functional Analytics (Retail Analytics, Supply Chain Analytics, Marketing Analytics, Customer Analytics, etc.)
• Working understanding of Statistical modelling & Time Series Analysis using Analytical tools (Python, PySpark, R, etc.)
• Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)
• Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference
• Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), database management systems
• Business intelligence & reporting (Power BI)
• Cloud computing services in Azure/ AWS/ GCP for analytics