What You Will Do

- Write, optimize, and execute SQL queries to extract data from relational databases and cloud data warehouses.

- Develop, run, and validate machine learning, predictive, or statistical matching models to uncover deeper consumer behaviors and forecast trends.

- Slice, unpivot, and aggregate raw transactional or panel data to calculate core business metrics such as household penetration, market share, and purchasing trends.

- Build and maintain clean, structured data tables and views that feed into recurring tracking reports and stakeholder dashboards.

- Review query outputs, perform data audits, and double-check logic to ensure accuracy and data integrity before insights are finalized.

- Use conditional logic and filtering techniques to segment data and isolate specific tracking cohorts.

- Clean, parse, and categorize unstructured or semi-structured text data.

- Translate technical data structures and query results into clear written summaries, bullet points,



or data tables for stakeholders in English-speaking environments.

Requirements

- 0 to 4 years of experience in Data Analysis, Business Analytics, or similar roles. Entry-level candidates with strong relevant coursework, personal data projects, or internships are welcome, as well as mid-level professionals with a proven track record of querying databases to drive business insights.

- Advanced English level (written and spoken).

- Foundational to intermediate SQL skills, including complex JOIN logic, standard aggregations, and CASE WHEN conditional logic.

- Python scripting for data cleaning, manipulation, and processing, with proficiency in pandas for complex multi-step transformations.

- Familiarity with modeling libraries such as scikit-learn or statsmodels to build and evaluate predictive or statistical matching models.

- Experience working with m

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