Sr. Manager Data Analytics-1

About us:

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers.

Working at Target means the opportunity to help all families discover the joy of everyday life. Caring for our communities is woven into who we are, and we invest in the places we collectively live, work and play. We prioritize relationships, fuel and develop talent by creating growth opportunities, and succeed as one Target team. At our core, our purpose is ingrained in who we are, what we value, and how we work. It’s how we care, grow, and win together.

A role in Merchandising Capabilities means partnering with Merchandising, technology, data science and analytics leaders to co-create solutions that maximizes business value and enables key strategies that are critical to the enterprise and for the experiences we create for our guests. Truly an owner and expert of your product and underlying processes, you will set the vision, align on the roadmap and mobilize teams to deliver needed outcomes. Given most strategies have a business impact, you will also serve as a trusted resource to guide other enterprise partners in their solutions to ensure the success and integrity of end-to-end deliverables.

As a Sr. Manager, Data Analytics in Merchandising,you will be accountableforsetting the vision, strategy, roadmap, and quality expectations for data,reporting, analytics, automation, and AI capabilitiesfor a specific business function within our Merchandising organization. You will serve as an advocate of our data-driven culture and a trusted advisor tobusiness leaders, helpingidentifywhereanalytics and AIcancreate the greatest business value.In partnership with your team of Data Analysts,you will translatebusinessprioritiesintoa portfolio of scalable solutions, ensure measurable outcomes,and buildaneffectiveanalyticsecosystemthatinformsandinfluencesdecisions. You will build a high-performingteam through talent pipeline planning, hiring, coaching, setting clear expectations, capability development, and performance management. You willpartner closely with Merchandising, Product Management, Data Science, Technology, and otheranalyticsteamsto align solutions, address capabilitygaps,and democratizetrusteddata and insights.

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

As a Sr.Manager,Data Analyticsfor Target'sMerch Data Analytics team you'll:

Lead an analytics team that supportsour world-class Merchandising leadership with data,insights,automation, and AI capabilitiesthat enable faster, smarter,and more scalable decision-making. Collaborate with stakeholders tounderstand their priorities androadmaps, translatebusiness problemsintoa clear portfolio of work, and hold the team accountable for delivering measurable business outcomes.

• Setthevision, strategy,androadmapfordata,reporting, analytics, automation, and AI capabilitiesfor thebusiness area, and prioritize work basedonbusinessvalue, urgency, scalability, and strategicalignment.
• Provide thought leadership in the application of data and analytics, helping business leaders identify opportunities where insights, automation, Generative AI, AI agents, or agentic AI can materially improve decisions and outcomes.
• Translatecomplexand ambiguous business problems into a portfolio of scalableanalytical and AI-enabled solutions,definingclearsuccessmeasuresandensuringthe team remains focused on business outcomes rather than isolated technical deliverables.
• Guide and challenge the team's analytical and solution-design approach, establishing expectations for technical quality, scalability, maintainability, and appropriateuseof statistical, analytical,andAI methods.
• Ensure the team has the capability to work effectively with large-scale datasets and modern data ecosystems, including platforms and technologies such as GCP BigQuery, Spark, SQL-based data warehouses, and data pipelines using Airflow or similar orchestration tools.
• Establish standards for evaluating and monitoring AI-driven analytical workflows, including defining appropriate quality metrics such as accuracy and relevance, assessing reliability, and measuring adoption and business impact of AI-enabled solutions.
• Identify and prioritize high-impact Generative AI opportunities and guide the adoption of AI-agent-enabled and agentic AI capabilities to automate repeatable analytical work, improve productivity, accelerate insight generation, and enable faster decision-making.
• Establish and promote responsible and scalable AI practices, including data privacy, governance, bias and risk considerations, explainability, human oversight, and integration with the broader data and analytics ecosystem.
• Ensureanalytical methodologies,AIsolutions,keyassumptions,evaluationapproaches,andreusablepatterns are appropriately documented to improve transparency, maintainability,knowledge sharing,andreuseacrosstheteam.
• Partner closely with Merchandising, Product Management, Data Science, Technology, and analyticspartners to align roadmaps, resolve dependencies, identify capability gaps,and democratizeaccesstotrusteddata and insights.
• Developtrusted relationships withbusiness leadersand communicatecomplexanalyticalandtechnical conceptsin clearbusiness terms, ensuring recommendations are actionable and connected to measurable business drivers.
• Build and lead a high-performingteam of approximately 8-10 analyststhrough talent pipeline planning, hiring, onboarding, coaching, performance management, succession planning, and career development.
• Developbothbusiness acumen and technicalcapabilitywithinthe team, fostering a culture of critical thinking, curiosity, experimentation, teaching, learning, collaboration, and continuous improvement.
• Ensure adherenceto corporate information protection and data governance standardsacross analytical and AI-enabled solutions.
• Staycurrenton industry trends, best practices, emerging analytical methodologies, modern data platforms, Generative AI, AI agents, and agenticAI,and determine where they can create meaningful value for Target.

About you:

• Undergraduate Degree in Information Technology, Computer Science, Data Science, Applied Mathematics, Statistics, or related quantitative discipline, or equivalentwork experience.
• Minimum of 12 years of experience in data analytics or related disciplines and a minimum of2 yearsofpeople management experience.
• Demonstrated experience leading analytics teams, setting direction and priorities, and delivering analytical solutions that influence meaningful business decisions.
• Strong ability to translate business strategy and ambiguous problems into an actionable analytics roadmap and to manage trade-offs across competing priorities and initiatives.
• StrongtechnicalfluencyacrossSQL,data warehousing and BIconcepts, large-scale data environments, and visualization platforms such as Power BI, Looker, Tableau, or equivalenttools; able to review, challenge,and guidetechnicalapproacheswithout being the primary hands-on executor.
• Strong understanding of modern data platforms and analytical ecosystems, including technologies such as GCP BigQuery, Spark, SQL-based warehouses, and workflow orchestration or data pipelines such as Airflow.
• Workingknowledgeofanalytical programming environments such as Python,R, Hive, or similarlanguages, alongwithstrongconceptual understanding of analyticaltechniques suchasregression, time-series analysis, classification, experimentation, and other methods used to identify and measure business drivers.
• Experience guiding teams in the use of Generative AI and LLM-based solutions, including prompt engineering, Retrieval-Augmented Generation (RAG), AI-assisted analytical workflows, AI agents, and agentic AI capabilities.
• Ability to assess AI-enabled solutions through appropriate measures of quality, reliability, relevance, adoption, and business impact, and to establish responsible AI practices including privacy, governance, bias and risk considerations, and explainability.
• Understanding of software development and analytical engineering practices including Git source code management, reusabledevelopment patterns, documentation, and Agilewaysof working.
• Strong problem-solvingand critical-thinkingskills, attention to detail,and ability to manage ambiguity and urgency in a fast-paced environment.
• Excellent communication, storytelling, service orientation,and relationship-buildingskills,with the ability to influence senior stakeholders and translate technical concepts into business implications and recommendations.
• Demonstrated ability to hire, coach, develop, and retain analytical talent and to build an environment that supports accountability, learning, knowledge sharing, and career growth.
• Experience with Retail, Merchandising, or Marketing isastrong add-on.

Useful Links-

Life at Target-https://india.target.com/

Benefits-https://india.target.com/life-at-target/workplace/benefits

Culture-https://india.target.com/life-at-target/diversity-and-inclusion