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