About the Role
Join the Data Analytics (DA) team at TII across domains such as Marketing and Digital, Merchandising, Supply Chain and Logistics, Store Operations, Finance and more . Here you'll collaborate with business leaders to turn data into insights that drive strategic decisions. You’ll be part of a fast-moving, high-impact environment focused on leveraging business intelligence and advanced analytics to solve real-world problems.
This role combines technical expertise with business understanding to uncover and communicate actionable insights using cutting-edge statistical and analytical techniques.
Behind one of the world’s best loved brands is a uniquely capable and brilliant team of data scientists, engineers and analysts. The Target Data & Analytics team creates the tools and data products to sustainably educate and enable our business partners to make great data-based decisions at Target. We help develop the technology that personalizes the guest experience, from product recommendations to relevant ad content. We’re also the source of the data and analytics behind Target’s Internet of Things (iOT) applications, fraud detection, Supply Chain optimization and demand forecasting. We play a key role in identifying the test-and-measure or A/B test opportunities that continuously help Target improve the guest experience, whether they love to shop in stores or at Target.com .
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
Requirements / About You
Experience: Overall 5-8 years exp and relevant 3-5 years exp
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
1. Extensive exposure to Structured Query Language (SQL), SQL Optimization and
DW/BI concepts.
2. Proven hands-on experience in BI Visualization tool (i.e. PBI, Looker, Tableau) with
ability to learn additional vendor and proprietary visualizations tools.
3. 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.
4. Hands on experience in R, Python, Hive or other open-source languages/database
5. Hands on experience in any advanced analytical techniques like Regression, Time-
series models, Classification Techniques, etc. and conceptual understanding of all
the techniques mentioned above
6. Git source code management & experience working in an agile environment.
7. Strong attention to detail, excellent diagnostic, and problem-solving skills
8. 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 urgency timelines
9. Competent and curious to ask questions and learn to fill gaps, desire to teach and
learn.
10. Excellent communication, service orientation and strong relationship building skills
11. Experience with Retail, Merchandising, Marketing will be strong addons
12. Hands-on experience leveraging Generative AI (GenAI) and LLM-based solutions
(e.g., prompt engineering, Retrieval-Augmented Generation – RAG) to enhance data
analysis, automate insight generation, and support business decision-making
13. 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.
