Data Analyst Officer

Investigate questions that span qualitative textual analysis and quantitative analysis. Identify trends, isolate anomalies, and drive to the root cause rather than stopping at the first correlation. Treat data quality as a named deliverable: freshness and volume checks, schema-change alerting, and lineage that makes it possible to trace any number in any deck back to its source. Maintain data documentation and dictionaries that stay current as the stack changes. Develop and present reports, charts, graphs, and tables for internal stakeholders, sub-companies, and third parties. Minimum Qualifications: 2+ years of industry experience in data handling, reporting, and analysis. BS or higher in data analytics, statistics, mathematics, or a related technical field or equivalent practical experience. Core Technical Skills Strong quantitative and analytical skills, with sound judgment about statistical significance, sample size, and confounding. Strong SQL (PostgreSQL, MySQL or similar): joins, window functions, CTEs, and query performance on large tables. Python or R with the relevant analytical libraries (e.g. pandas, numpy, statsmodels, scikit-learn, or the tidyverse equivalents). Experience with BI or analytical software such as QuickSight, Tableau, Power BI, Looker, or Metabase. Practical fluency with AI tooling in the analytics workflow, using LLMs and embeddings for text analysis, code assistance, and exploratory work, alongside a clear-eyed view of where these tools fail and how to catch it. Nice to Have AWS data workflow : Lake Formation, Glue, Crawler, Data Catalog, and Athena. Experience with lakehouse table formats (Iceberg, Delta, or Hudi) and layered data architectures (raw, transformed, curated). Working knowledge of GA4, server-side tracking, and multi-touch or cross-platform attribution, including its limits. Understanding of how AI-driven discovery is reshaping publisher traffic AI summaries, zero-click search, referrals from conversational assistants, and how to measure it.