Lead Data Analyst

About the Role
Join the Data Analytics (DA) team at TII across domains such as Marketing and Digital, Merchandising, Supply Chain and Logistics, Store Operations, Finance and more. Here you'll collaborate with business leaders to turn data into insights that drive strategic decisions. You’ll be part of a fast-moving, high-impact environment focused on leveraging business intelligence and advanced analytics to solve real-world problems.
This role combines technical expertise with business understanding to uncover and communicate actionable insights using cutting-edge statistical and analytical techniques.
Behind one of the world’s best loved brands is a uniquely capable and brilliant team of data scientists, engineers and analysts. The Target Data & Analytics team creates the tools and data products to sustainably educate and enable our business partners to make great data-based decisions at Target. We help develop the technology that personalizes the guest experience, from product recommendations to relevant ad content. We’re also the source of the data and analytics behind Target’s Internet of Things (iOT) applications, fraud detection, Supply Chain optimization and demand forecasting. We play a key role in identifying the test-and-measure or A/B test opportunities that continuously help Target improve the guest experience, whether they love to shop in stores or at Target.com.
Key Responsibilities:
 Demonstrate thought leadership in the application of data, analytics, and AI to
influence merchandising strategy and outcomes
 Independently translate ambiguous business problems into structured analytical
approaches, including scenario, decision, and action modelling
 Partner with Target business stakeholders to understand priorities and roadmaps,
validate analytical requirements, and present insights and recommendations with
clarity and impact
 Design, develop, and deliver analytical and AI-driven solutions (including GenAI,
Agent, and Agentic approaches) that enable decision support, forecasting,
optimization, and automation
 Apply advanced analytics techniques, including causal, predictive, and prescriptive
analytics, to drive deeper understanding of business levers and inform optimal
actions
 Work with large-scale datasets using platforms such as GCP BigQuery, Spark, and
SQL-based data warehouses; build and maintain reliable data pipelines using Airflow
or similar orchestration tools
 Evaluate and monitor AI-driven analytical workflows, defining quality metrics (e.g.,
accuracy, relevance), assessing reliability, and measuring tangible business impact
 Synthesize complex analyses into compelling narratives; act as a strong storyteller
who can influence executive and merchant audiences using data
 Develop strong business acumen and cultivate trusted relationships with internal
clients and partners
 Create high-quality analytical and AI solution artifacts, documenting methodologies,
assumptions, models, and decision logic
 Contribute to knowledge-sharing systems that support reuse, iteration, and
continuous improvement of analytical models and approaches
 Ensure compliance with corporate data protection standards and embed responsible
AI practices, including data privacy, bias mitigation, and explainability
 Stay current with industry trends, emerging methodologies, and best practices in
analytics, AI, and retail decision science