Lead Data Analyst

As a Lead Data Analyst, you'll be a key influencer in driving our data analysis strategy, leading complex projects, and mentoring a team of analysts. This is an exceptional opportunity to shape the future of data within the organization, working on high-impact initiatives for our Merchandising, Supply Chain, Marketing, IBP and Stores teams that directly contribute to business success through deep analytical rigor and actionable insights. If you're a visionary data leader with a passion for innovation, statistical modeling, and translating complexity into clear business value, we encourage you to apply.

• This position is fully remote
• This role is an Individual Contributor position
  
  

A day in the life as a Lead Data Analyst...

• Lead the analysis of complex, high-impact business problems across Merchandising, Supply Chain, Marketing, IBP and Stores using advanced statistical and analytical methodologies, providing critical insights and recommendations to decision-makers
• Identify and interpret critical trends, patterns, anomalies, or inconsistencies in massive and complex datasets to drive key improvements and strategic initiatives
• Design and implement A/B tests and experimental designs to measure the impact of strategic changes, ensuring rigorous methodology and valid conclusions
• Design, develop, and maintain advanced analytical models and data structures (e.g., feature engineering, ETL logic, analytical tables) to support complex business requirements and reporting needs
• Lead and mentor a team of data analysts, providing guidance, training on analytical techniques, and support to enhance their technical and storytelling skills
• Collaborate with data engineering and product teams to define data requirements and ensure the integrity and accessibility of data sources used for analysis
• Actively participate in and champion team ceremonies (Scrum/Kanban) contributing to the successful delivery of sprint goals and continuous process improvement in the analytics pipeline
• Establishes and champions high standards for knowledge management and documentation of analytical methodologies, data sources, and model definitions, significantly enhancing team efficiency and reproducibility
• Stay up-to-date with the latest statistical methodologies, machine learning trends, and data technologies, proactively identifying opportunities for improvement and innovation in the analytics space
  
  

What You'll Bring To The Table...

• Expert-level proficiency in SQL for advanced data manipulation, data preparation, querying complex relational and non-relational databases, and optimizing query performance
• Advanced application of Data Visualization tools (e.g., Tableau, Power BI, Looker) for designing and implementing complex, interactive dashboards and analytical storytelling
• Extensive knowledge of Advanced Statistical Analysis and Modeling, including regression analysis, time-series forecasting, hypothesis testing, and causal inference
• Ability to design and develop sophisticated and interactive data visualizations and executive-level dashboards that translate analytical findings into clear, actionable business narratives
• Proven expertise in Data Mining and cleaning techniques for extracting strategic insights from large and complex datasets using languages like Python or R
• Advanced skills in Predictive Modeling for developing highly accurate forecasting models and scenario planning tools (e.g., using libraries like scikit-learn or pandas)
• Exceptional collaboration, influence, and communication skills, with the ability to effectively communicate complex analytical concepts and influence decision-making at all levels of the organization
  
  

We'd love to hear from you if you have...

• 8 years of professional experience in a hands-on Data Analyst or Analytical role
• Bachelor's degree in Data Science, Information Systems, Mathematics, Statistics, Business Analytics or a related quantitative field (or equivalent practical experience)
• Proven experience leading the delivery of complex analytical projects and models in an agile environment
• Strong proficiency in one or more statistical programming languages (e.g., Python or R) for advanced data manipulation and modeling