Data Scientist - Retail

General Position Definition

• This role will drive analytics and data science for one or more of Shell’s Retail business teams
• The ideal candidate is passionate about delivering commercial value and insights through Retail Analytics and Data Science
• We help the business team’s answer some of the following questions:
  • What is the right assortment and mix of products to drive category growth?
  • How responsive are our products to price changes?
  • Which of our competitors impact our sales and pricing?
  • How can we improve the customer experience at our outlets?
  • Which customers are most likely to churn?
• Candidate should be able to ask the right questions, ability to move from data to insight to action, break down strategic & operational questions from different Retail teams and structurally answer them with data driven insights
• Incumbent is responsible for working on a range of technologies and tools collaborating directly with the Retail stakeholders & other partners

Education Requirement/Field of Study :

• Minimum 5-7 years of relevant experience in Retail Analytics
• Preferred experience in Retail, CPG or E-commerce
• Good interpersonal communication skills and influencing skills
• Eagerness to learn and ability to work with limited supervision
• Advanced university degree in Mathematics, Statistics, Engineering, Economics, etc.

Requirements : Skills

• Provide deep business expertise in Retail/CPG businesses:
  • Category Analytics:Range reviews, Assortment planning, identifying trends and patterns in category performance, new product launches
  • Pricing Analytics: UnderstandingPrice elasticity, evaluating impact of competitor pricing, impact of pricing changes on margins
  • Marketing and Promotion Analytics: Campaign design and promo effectiveness testing, churn prediction, cross-sell / up-sell, Market Basket Analysis, Customer segmentation, propensity analysis, customer lifetime value, market mix modeling
  • Store Analytics: Leverage data and visualization to create actionable insights for on ground store teams, territory and district managers
• Should have strong story telling skills: Ability to explain complex data and models to business teams
• Proficiency Level: Mastery

Stakeholder Engagement Skills

• Working collaboratively across multiple sets of stakeholders – business SMEs, IT, Data teams, Analytics resources to deliver on project deliverables and tasks
• Identify actionable insights that directly address Retail Team’s challenges / opportunities
• Articulate business insights and recommendations to respective stakeholders
• Understanding business KPI's, frameworks and drivers for performance
• Proficiency Level: Mastery

Technology Skills

• Strong experience in specialized analytics tools and technologies (including, but not limited to)
  • Azure Databricks, Alteryx
  • Power BI, Spotfire or other visualization tools
  • Python, R
• Statistics / Machine Learning: Data Quality Analysis, Exploratory data analysis, Hypothesis testing, Univariate / Multivariate Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Affinity & Association, Time Series, Decision Trees, sentiment analysis, Clustering
• Identify the right approach(es) for given scenario and articulate why the approach fits
• Assess data availability and modeling feasibility
• Proficiency Level: Skill-to-Mastery

Special Challenges

• Easily analyzes, draws and synthesizes important insights from complex data.
• Extremely curious and self-driven to understand business performance through data.
• Ability to translate a business question into a well-defined analytical plan that includes data requirements for technical resources to extract the necessary data.
• Rapid onboarding on projects, understanding analytics goal and working with ill-defined datasets
• Communicating technical jargon in plain English to colleagues within Data Science team and outside
• Virtual working with network of colleagues located throughout the globe

Interested?