Data Analyst

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.

Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.

Overview about TII

At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.

Fulfillment Optimization Analytics team supports Target’s middle-mile fulfillment and LM delivery business. The team
focuses on optimizing how orders are fulfilled and delivered by balancing speed, cost, and guest experience across the
network.

About the Role

As a Data Analyst, you will help shape last-mile fulfillment strategy by identifying opportunities and solving business
problems using data. You will analyze data, generate insights, and build analytical solutions to support decision-making
and drive improvements in speed, cost, and reliability. This is a high-impact role that requires working closely with cross-functional stakeholders across business, product, and engineering.

Key Responsibilities
 Partner with business and product teams to deliver data-driven insights and scalable analytics solutions.
 Develop analytics solutions to support strategic initiatives, enabling effective measurement, reporting, and timely
course correction of business strategies
 Leverage SQL and data visualization tools to analyze structured and unstructured data.
 Apply statistical techniques and basic machine learning techniques to measure business drivers
 Translate complex analyses into clear, actionable recommendations for stakeholders
 Continuously explore and adopt new tools, technologies, and methodologies
 Drive end-to-end analyses, from problem definition to insight generation and stakeholder communication.

Qualifications
 Education
o A Bachelor’s degree in Engineering (B.Tech/B.E.) or a Master’s degree in Statistics, Econometrics,
Mathematics, or a related field is required.
 Experience
o Candidates should have 2–6 years of total professional experience, with 1–3 years of relevant hands-on
experience in analytics.
Technical Skills
 Proficiency in SQL (joins, volatile tables, basic query optimization)
 Strong understanding of data modeling and business intelligence concepts.
 Experience with BI tools such as Tableau, Domo, MicroStrategy, or Qlik
 Programming experience in Python, R, or similar open-source technologies
 Understanding of analytical techniques such as regression, time-series analysis, and classification methods.
 Familiarity with databases: Teradata, Oracle, Hive
 Familiarity with GenAI tools and techniques (e.g., LLMs, prompt engineering, or AI-assisted analytics workflows)
is preferred.