Sr Data Analyst

Job Summary

As a Senior Data Analyst for Targets IT Data Platform Analytics team youll:

Support Target Technology leaders and teams with critical data analysis and insights that enable faster, smarter and more scalable decisions across Targets technology ecosystem. Collaborate with stakeholders to understand priorities, roadmap, and outcomes, and use data, analytics, and AI to improve technology visibility, reliability, risk management, and operational decision-making.

Responsibilities

• Interface with Target Technology representatives, Product Managers, and engineering partners to validate business and technology requirements for analysis and present final analytical results.
• Design, develop, and deliver analytical and AI (GenAI, Agent, Agentic) driven solutions that result in decision support, predictive insights, and scalable technology intelligence.
• Work with large-scale technology datasets using tools such as SQL-based warehouses, GCP BigQuery, Spark, or similar data platforms and pipelines.
• Build and maintain analytical dashboards and self-service experiences primarily in Looker (with Power BI or similar tools as needed), using governed metrics and reusable analytical models.
• Evaluate and monitor AI-driven analytical workflows, including defining quality metrics such as accuracy and relevance, assessing reliability, and measuring business impact of AI-enabled solutions.
• Gather required data and perform exploratory, diagnostic, and statistical analysis to identify trends, anomalies, relationships, root causes, and emerging technology risks.
• Apply advanced analytical techniques such as regression, time-series analysis, classification, forecasting, anomaly detection, segmentation, or other appropriate methods to technology problems.
• Contribute to the development, validation, and monitoring of analytical frameworks such as Change Risk Score, predictive alerting, technology health signals, and other proactive insight capabilities.
• Use Python, R, or similar analytical tools to prototype models, automate analysis, engineer features, and evaluate statistical or machine-learning approaches.
• Translate analytical and scientific methodologies into clear business and technology terms, and present findings in a manner that technology partners and leaders can understand and act upon.
• Document AI solutions, analytical methodologies, assumptions, metric definitions, and model evaluation approaches used in analytical projects.
• Participate in knowledge sharing and iterative model-building practices, contributing reusable analytical patterns, documentation, and lessons learned.
• Ensure compliance with corporate data protection standards and incorporate responsible AI practices, including data privacy, bias mitigation, explainability, and appropriate use of AI-driven solutions.
• Partner with data engineering and platform teams to understand data lineage, quality, dependencies, and source-system context, and improve trust in analytical outputs.
• Keep up to date on technology analytics, data science, GenAI, agentic AI, and emerging methodologies, and identify opportunities to apply them to ITDP use cases.

About You

• Experience: Overall 5-8 years exp and relevant 3-5 years exp
• Qualification: B.Tech / B.E. or Masters in Statistics /Econometrics/Mathematics equivalent
• Extensive exposure to Structured Query Language (SQL), SQL optimization, data warehousing, and BI concepts.
• Proven hands-on experience in BI visualization tools (i.e. Looker, Power BI, Tableau) with ability to learn additional vendor and proprietary visualization tools.
• Strong knowledge of structured and unstructured data stores and extensive hands-on experience working with large, complex datasets.
• Hands-on experience in Python, R, or other open-source languages and analytical environments
• Hands-on experience with advanced analytical techniques such as Regression, Time-series models, Classification, Forecasting, Anomaly Detection, or similar methods, with conceptual understanding of when to apply each technique.
• Git source code management and experience working in an agile environment.
• Strong attention to detail with excellent diagnostic, analytical, and problem-solving skills; ability to work through ambiguous technology problems using structured thinking.
• Highly self-motivated with a strong sense of urgency and ability to work independently and in team settings in a fast-paced environment.
• Competent and curious to ask questions, learn quickly, fill gaps in domain knowledge, and share knowledge with others.
• Excellent communication, service orientation,

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.