Business Intelligence Data Analyst
Insight Global
Job Description
WHO YOU’LL WORK WITH
- You will join the North America Digital Operations organization for one of our major retail clients. This team specializes in identifying operational inefficiencies, elevating consumer experiences, and informing data‑driven decisions that increase demand and protect profitability across the North America marketplace.
- This role supports the Digital Loss Prevention (DLP) function and collaborates closely with:
- Gift Card Operations
- DLP Quality Assurance
- Fraud Insights teams
- Together, these groups work to reduce friction, detect risk, safeguard revenue, and enhance the consumer journey across digital touchpoints.
WHO WE ARE LOOKING FOR
- We are seeking a versatile, self‑directed Business Intelligence Analyst who thrives in ambiguous environments and can perform deep‑dive analyses to uncover operational gaps that impact financial performance.
- You should be comfortable navigating multiple internal systems, understanding how data flows through frontline tools and transactional platforms, and connecting signals across a complex ecosystem. The ideal candidate is highly data‑literate, learns quickly, and can translate analytical findings into clear, actionable recommendations that drive clarity, reduce risk, improve consumer experiences, and protect the business.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Skills and Requirements
WHAT YOU’LL WORK ON
In this role, you will support Gift Card Operations and Direct Digital Loss Prevention across the North America business.
Responsibilities include:
- Using data to identify risks, inefficiencies, trends, and opportunities that improve operational effectiveness
- Producing insights to help generate incremental demand, reduce friction in the digital consumer experience, and safeguard revenue streams
- Managing end‑to‑end ownership of dashboards, reporting tools, and data products with a focus on accuracy, agility, and ease of interpretation
- Working through ambiguity to solve open‑ended business problems using all available datasets
- Partnering across digital operations, fraud, and QA teams to ensure alignment and quality in analytical outputs
- This role offers broad exposure to digital operations, fraud prevention, and enterprise‑scale data flows within a global retail environment.
QUALIFICATIONS — WHAT YOU BRING
- Bachelor’s degree in Statistics, Mathematics, Computer Science, Economics, or related field
OR 2–3 years of relevant analytical work experience
Technical Skills
- SQL: Required for querying and manipulating large datasets
- Excel: Strong working proficiency
- Data Visualization: Experience with Tableau, Power BI, or similar tools
- Programming (Preferred but not required): Python or R for richer analysis or automation
Core Competencies
- Strong analytical thinking and problem‑solving skills
- Ability to translate complex data into simple, actionable insights
- Effective communication across technical and non‑technical partners
- High attention to detail, curiosity, and eagerness to learn new systems and processes
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