Sr. BI Analyst

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

The Role

General Position Definition

• This role will drive reporting analytics and data analysis 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 Business Intelligence.
• Ideal candidate will work on:
• Engaging the stakeholders to understand the business problem and gather requirements
• Data extraction and reporting using different tools and techniques like Alteryx, SQL, R/Python etc
• Generate insights from the data and effective story boarding.
• Ability to identify and suggest key performance indicators for the stakeholders.
• Responsible for maintaining the reporting requirements
• Regularly interact with stakeholders/business owners and present actionable insights from the dashboards.
• 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
• Should have intensive experience in Business Intelligence – creating dashboards, providing business performance insights and storyboarding the outcome.
• Incumbent is responsible for working on a range of technologies and tools collaborating directly with the Retail stakeholders & other partners

Skills

Industry / Functional Expertise

• 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: Understanding Price 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: Intermediate

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/SQL
• Power BI, Spotfire or other visualization tools
• Python/ R
• Reporting skills: Data collection, Data cleaning, Data Quality Analysis, Exploratory data analysis, Reporting Automation, Uni variate analysis, Bi-variate analysis, Data visualization, Dashboard maintenance and leverage various reporting tools
• Should be strong at understanding data architecture or frameworks.
• Assess data availability and reporting/modelling feasibility
• Proficiency Level: Skill-to-Mastery

Special Challenges

• Easily analyzes, draw and synthesizes important insights from complex data.
• Identify relevant data sources available and pro-actively suggest on integration of various data sources to drive business requirements.
• 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

Experience

• Minimum 5-7 years of relevant experience in Retail Analytics
• Should have strong experience in delivering dashboards with at least one of the technologies POWERBI/SPOTFIRE/QLIK
• 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