Sr Data Analyst - Planning & Inventory Management

Target Target · Retail · Minneapolis, MN

Sr Data Analyst role focused on leveraging advanced analytics, AI, and GenAI/Agentic approaches for planning and inventory management. The role involves translating business problems into analytical solutions, applying techniques like RAG and agent workflows, working with large datasets on platforms like GCP BigQuery, and ensuring the quality and impact of AI-driven outputs. The goal is to improve inventory availability, forecasting accuracy, and optimize inventory investments.

What you'd actually do

  1. Develop and deliver analytical and AI-driven solutions (including GenAI, Agent, and Agentic approaches) that enable decision support, forecasting, optimization, and automation
  2. Apply advanced analytics techniques, including causal, predictive, and prescriptive analytics, to drive deeper understanding of business levers and inform optimal actions
  3. Partner with Target business stakeholders to understand priorities and roadmaps, validate analytical requirements, and present insights and recommendations with clarity and impact
  4. 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
  5. Contribute to AI-driven analytical workflows, defining quality metrics (e.g., accuracy, relevance), assessing reliability, and measuring tangible business impact

Skills

Required

  • SQL
  • SQL Optimization
  • DW/BI concepts
  • BI Visualization tool (i.e. Power BI, Looker, Tableau)
  • structured (i.e. Teradata, Oracle, Hive) and unstructured databases including Hadoop Distributed File System (HDFS)
  • large data sets
  • R
  • Python
  • Hive
  • Regression
  • Time-series models
  • Classification Techniques
  • Git source code management
  • agile environment
  • attention to detail
  • diagnostic skills
  • problem-solving skills
  • self-motivated
  • sense of urgency
  • work independently
  • work in team settings
  • fast-paced environment
  • manage urgency timelines
  • ask questions
  • learn to fill gaps
  • teach and learn
  • communication skills
  • service orientation
  • relationship building skills

Nice to have

  • Retail
  • Merchandising
  • Marketing
  • Generative AI (GenAI)
  • LLM-based solutions
  • prompt engineering
  • Retrieval-Augmented Generation – RAG
  • AI-agent workflows
  • GCP BigQuery
  • Spark
  • Airflow

What the JD emphasized

  • AI-driven solutions
  • GenAI
  • Agent
  • Agentic approaches
  • advanced analytics techniques
  • causal, predictive, and prescriptive analytics
  • AI-driven analytical workflows
  • Generative AI (GenAI)
  • LLM-based solutions
  • Retrieval-Augmented Generation – RAG
  • AI-driven tools
  • AI-agent workflows

Other signals

  • Develop and deliver analytical and AI-driven solutions (including GenAI, Agent, and Agentic approaches)
  • Apply advanced analytics techniques, including causal, predictive, and prescriptive analytics
  • Contribute to AI-driven analytical workflows, defining quality metrics
  • Experience leveraging Generative AI (GenAI) and LLM-based solutions (e.g., prompt engineering, Retrieval-Augmented Generation – RAG)
  • Ability to integrate AI-driven tools and AI-agent workflows into end-to-end analytical processes