Senior Data Analyst - TES Data and Analytics

TargetBrooklyn Park, MN
Hybrid

About The Position

The Data & Analytics Team supporting Target Enterprise Services (TES) is seeking a detail-oriented and innovative Senior Data Analyst. This role involves more than just traditional data analysis; it requires a proactive individual capable of identifying process inefficiencies, developing impactful tools, and designing metrics to drive decision-making and continuous improvement. The Senior Data Analyst will be hands-on in analyzing data, prototyping models, and collaborating with cross-functional teams to design, build, and enhance the effectiveness of multiple data products. The role focuses on delivering actionable insights, building scalable tools, and mentoring team members, all while driving analytics that shape business decisions. This position is ideal for someone who thrives in a fast-paced environment, enjoys complex challenges, and can balance analytical rigor with creativity. Core responsibilities are outlined within this job description, and job duties may change at any time due to business needs.

Requirements

  • Bachelor’s degree in Data Science, Business Analytics, Statistics, or related field.
  • 5+ years of experience in data analytics, with a track record of solving complex business problems.
  • Advanced skills in tools and programming languages such as SQL, Python, R, and data visualization tools (e.g., Looker, Power BI).
  • Practical experience leveraging large language models and AI prompt engineering to help analyze and categorize data.
  • Proven experience in developing metrics, KPIs, and reporting frameworks.
  • Ability to translate data into actionable insights and effectively communicate findings to stakeholders.
  • Strong analytical mindset with the ability to identify root causes and recommend solutions.
  • Ability to work across both modern and immature data.
  • Excellent collaboration skills and experience working with cross-functional teams.
  • Continually updates knowledge of new and evolving technologies via formal training and self-directed education to continue to raise individual and team performance.

Nice To Haves

  • Familiarity with service center analytics.
  • Experience building statistical models or algorithms to improve forecasting.
  • Knowledge of systems like GCP, Looker, Power BI, and Git.
  • Demonstrated ability to mentor and support junior team members in analytics.

Responsibilities

  • Identify and analyze process gaps using data exploration, intuition, and investigative techniques.
  • Conduct deep-dive analyses to uncover inefficiencies and propose data-driven solutions to business problems and workflows.
  • Perform trade-off analyses to guide decision-making and improve overall organizational performance.
  • Apply AI-enabled analysis techniques to accelerate high-quality analysis, transform unstructured and immature data sources into scalable insights, identify emerging themes, and pressure-test hypotheses while applying strong analytical judgment, validation, and responsible use practices.
  • Build prototype statistical models and algorithms to enhance forecasting accuracy and operational effectiveness.
  • Support development of topic modeling and sentiment analysis capabilities, bringing structured metadata to unstructured open text sources.
  • Develop user-friendly tools and dashboards to serve up actionable insights to service center and enterprise partner teams.
  • Ensure analytical solutions are scalable and integrated into team workflows for lasting impact.
  • Create KPIs, metrics, and calculations that accurately measure performance and shape desired behaviors across the Service Center Organization.
  • Partner with enterprise analytics teams to ensure cohesiveness and consistency across the reporting portfolio.
  • Regularly review and refine metrics to reflect evolving business needs and priorities.
  • Partner with analysts and stakeholders across data and analytics teams to align on goals, methods, and outputs.
  • Act as a thought leader by sharing domain knowledge, best practices, and analytical techniques to elevate team performance.
  • Support the alignment of insights with business goals by fostering strong cross-functional relationships.
  • Translate complex analytics into clear, actionable business insights tailored to stakeholders’ needs.
  • Effectively communicate findings through compelling presentations, data visualizations, and storytelling.
  • Provide guidance on trade-offs between competing priorities and decisions using a data-driven approach.

Benefits

  • Comprehensive health benefits and programs (medical, vision, dental, life insurance)
  • 401(k)
  • Employee discount
  • Short term disability
  • Long term disability
  • Paid sick leave
  • Paid national holidays
  • Paid vacation
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