Senior Data Analyst

As a Sr Data Analyst for Target's Data Analytics team you'll support our world-class leadership team at Target with critical data analysis that helps business teams make profitable decisions. Enable faster, smarter, and more scalable decision-making to compete and win in the modern retail market. Collaborate with stakeholders and understand their priorities and roadmaps to drive business strategies using data.

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 such as accuracy and 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

Requirements / About You:

• Experience: Overall 5-8 years of experience and relevant 3-5 years of experience
• Qualification:
• TI: B.Tech / B.E. or Masters in Statistics / Econometrics / Mathematics equivalent
• US: BA/BS in a quantitative degree - Math, Statistics, Econometrics, Data Sciences, Computer Science, or equivalent work experience

Skills required:

• Extensive exposure to Structured Query Language (SQL), SQL optimization, and DW/BI concepts
• Proven hands-on experience in BI visualization tools such as PBI, Looker, and Tableau, with ability to learn additional vendor and proprietary visualization tools
• Strong knowledge of structured databases such as Teradata, Oracle, and Hive, and unstructured databases including Hadoop Distributed File System (HDFS); exposure and extensive hands-on work with large datasets
• Hands-on experience in R, Python, Hive, or other open-source languages/databases
• Hands-on experience in advanced analytical techniques like regression, time-series models, classification techniques, etc., and conceptual understanding of all the techniques mentioned above
• Git source code management and experience working in an agile environment
• Strong attention to detail, excellent diagnostic, and problem-solving skills
• Highly self-motivated with a strong sense of urgency to be able to work both independently and in team settings in a fast-paced environment; capability to manage urgent timelines
• Competent and curious to ask questions and learn to fill gaps; desire to teach and learn
• Excellent communication, service orientation, and strong relationship-building skills
• Experience with retail, merchandising, and marketing will be strong add-ons
• Hands-on experience leveraging Generative AI (GenAI) and LLM-based solutions such as prompt engineering and Retrieval-Augmented Generation (RAG) to enhance data analysis, automate insight generation, and support business decision-making
• Ability to integrate AI-driven tools and AI-agent workflows into end-to-end analytical processes, enabling automation, improving productivity, and scaling analytics use cases