Data Analyst

Description

Summary: A Data Analyst turns data into insights, collecting and cleaning data, building analyses, performing statistical analyses, and communicating findings to support business decisions. Highlights: 1. Transform data into insights to support business decisions 2. Develop and maintain analytical models and dashboards 3. Collaborate with teams to improve data pipelines and measurement **Data Analyst — Job Description** **Overview** A Data Analyst turns data into insights that support business decisions. They collect and clean data, build analyses and dashboards, perform statistical analyses, and communicate findings to stakeholders. **Key Responsibilities** * Collect, clean, and transform data from multiple sources (databases, spreadsheets, APIs). * Build and maintain dashboards and reports for KPIs and performance tracking. * Perform exploratory data analysis (EDA), segmentation, and trend/variance analysis. * Create queries and data extracts; ensure data quality and accuracy. * Develop and maintain analytical models (descriptive and, in some roles, predictive). * Run A/B tests or experiments (where applicable) and interpret results. * Identify data issues, root causes, and improvement opportunities. * Document data definitions, assumptions, and analysis methodology. * Present insights clearly to non\-technical stakeholders; recommend actions. * Collaborate with engineering/BI teams to improve data pipelines and measurement. **Required Qualifications** * Experience in data analysis (internship or professional). * Strong SQL skills and ability to write/optimize queries. * Proficiency with spreadsheet tools (Excel/Google Sheets) and/or BI/reporting tools. * Working knowledge of statistics and metrics/KPIs. * Familiarity with data visualization and storytelling (e.g., Power BI, Tableau, Looker). * Ability to communicate insights and attention to detail for data quality. **Preferred Qualifications** * Experience with Python or R for analysis (pandas, numpy, scikit\-learn, etc.). * Experience with ETL/ELT pipelines and data warehousing concepts. * Familiarity with data modeling (star schema, dimensional modeling) and data governance basics. * Experience with business domains (finance, retail, operations, product analytics, marketing, etc.). * Stakeholder\-facing experience and experimentation/A\-B testing exposure. Pay: RO840\.250 \- RO1,295\.220 per month Work Location: In person