Sr Data Analyst - Planning & Inventory Management

The pay range is $88,000.00 - $158,000.00

Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.

About us:

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.

As a Sr Data Analyst for Target’s Planning & Inventory Management, Data Analytics team you’ll leverage data, analytics, and insights to support critical business capabilities including Assortment & Inventory Planning, Forecast Management, In-Season Management, Key Event Management, and Strategy & Enablement. This role partners across planning, inventory, merchandising, and technology teams to transform data into actionable insights and provides recommendations that improve inventory availability, enhance forecasting accuracy, optimize inventory investments, and support profitable growth. Through advanced analytics, reporting, and performance measurement, you will help deliver a joyful Guest experience while enabling efficient inventory management and enterprise decision-making.

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs. 

Key Responsibilities:

• Translate business problems into well-defined analytical questions and structured approaches

• Support scenario, decision, and action modelling to evaluate business trade-offs and inform recommended actions

• Partner with Target business stakeholders to understand priorities and roadmaps, validate analytical requirements, and present insights and recommendations with clarity and impact

• 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

• Contribute to AI-driven analytical workflows, defining quality metrics (e.g., accuracy, relevance), assessing reliability, and measuring tangible business impact

• Ensure analytical outputs are accurate, scalable, and aligned with business context

• Develop strong data storytelling skills to communicate insights and recommendations to non-technical audiences

• Document analytical methodologies, assumptions, and outputs to support reuse and knowledge sharing

• Adhere to corporate data protection standards and responsible AI practices

About You:

• BA/BS or equivalent experience (Math, Statistics, Econometrics, Data Sciences, Computer Science, etc.) or equivalent work experience

• 3+ years of work experience in data analysis or masters level education in business analytics, data science, etc.

• Extensive exposure to Structured Query Language (SQL), SQL Optimization and DW/BI concepts

• Proven hands-on experience in BI Visualization tool (i.e. Power BI, Looker, Tableau) with ability to learn additional vendor and proprietary visualizations tools

• Strong knowledge of structured (i.e. Teradata, Oracle, Hive) and unstructured databases including Hadoop Distributed File System (HDFS). Exposure and extensive hands-on work with large data sets

• Experience in R, Python, Hive or other open-source