Senior Data Analyst at Target

Short Description:

The Senior Data Analyst position at Target's Merch Data Analytics team involves supporting Merchandising leadership by providing critical data analysis for informed decision-making. The role requires collaboration with stakeholders, validation of business requirements, and the design and delivery of analytical solutions. The analyst will evaluate processes, interpret statistical data, and contribute to building business acumen. Qualifications include 5-8 years of overall experience with 3-5 years in Machine Learning, proficiency in SQL, exposure to BI visualization tools, and hands-on experience with large datasets. Strong communication skills, attention to detail, and the ability to work in a fast-paced environment are essential, with experience in Retail or Merchandising considered a valuable asset.

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Position: Senior Data Analyst

Location: Target Corporation India Pvt. Ltd., Bangalore, Karnataka, India, 560045

Job ID: R0000288803

Job Family: Business Intelligence Reporting & Analytics

Schedule: Full Time

As a Senior Data Analyst within Target's Merch Data Analytics team, you will:

Support Target's Merchandising leadership team by conducting essential data analyses that facilitate informed decision-making for the Merch business team. Contribute to achieving faster, more intelligent, and scalable decision-making processes to stay competitive in the evolving retail market. Collaborate with stakeholders, aligning with their priorities and roadmaps to drive business strategies through data insights.

Interface with Target business representatives to validate business requirements and requests for analysis, presenting final analytical results. Design, develop, and deliver analytical solutions that contribute to decision support or models. Gather necessary data and perform comprehensive data analyses to meet business needs, effectively communicating the impact of proposed solutions to business partners.

Evaluate processes, analyze, and interpret statistical data, developing business acumen and fostering client relationships. Present results in a manner understandable to business partners, translating scientific methodologies into business terms. Document analytical methodologies used in executing analytical projects and actively participate in knowledge-sharing systems to support iterative model builds. Adhere to corporate information protection standards.

Stay abreast of industry trends, best practices, and emerging methodologies.

Qualifications:

• TI: B.Tech/B.E. or Masters in Statistics/Econometrics/Mathematics or equivalent
• US: BA/BS in a quantitative degree – Math, Statistics, Econometrics, Data Sciences, Computer Science, or equivalent work experience

Requirements / About You:

• 5-8 years overall experience with 3-5 years of relevant experience, including work on Machine Learning (ML)
• Extensive exposure to Structured Query Language (SQL), SQL Optimization, and DW/BI concepts
• Hands-on experience with BI Visualization tools (e.g., Tableau, Domo, MSTR10, Qlik) with the ability to learn additional vendor and proprietary visualization tools
• Strong knowledge of structured (e.g., Teradata, Oracle, 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 such as Regression, Time-series models, Classification Techniques, etc., with a conceptual understanding of all mentioned techniques
• 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, capable of working independently and in team settings in a fast-paced environment
• Excellent communication, service orientation, and strong relationship-building skills
• Experience in Retail, Merchandising, or Marketing is a strong advantage.

Please click here to apply.