Senior Data Analyst

A Senior Data Analyst is responsible for collecting, analyzing, and interpreting complex data to help organizations make strategic business decisions. This role goes beyond reporting—it involves advanced analytics, data modeling, and providing actionable insights that drive performance, efficiency, and growth.Key ResponsibilitiesLead end-to-end data analysis projects across business functionsCollect, clean, and validate large datasets from multiple sourcesBuild and maintain dashboards, reports, and performance metricsPerform advanced statistical and trend analysis to identify insightsTranslate business requirements into analytical solutionsPresent findings and recommendations to stakeholders and leadershipDevelop predictive models and forecasting toolsCollaborate with engineering, product, finance, and marketing teamsEnsure data quality, accuracy, and consistency across systemsMentor junior analysts and support analytics best practicesRequired QualificationsBachelor’s degree in Statistics, Data Science, Computer Science, Economics, or related field5–8+ years of experience in data analysis or business intelligenceStrong proficiency in data querying and manipulation using SQLExperience with programming tools such as Python or RExpertise in data visualization tools like Tableau or Microsoft Power BIStrong analytical thinking and problem-solving skillsExcellent communication and data storytelling abilitiesPreferred QualificationsMaster’s degree in Data Science, Statistics, or related fieldExperience with machine learning or predictive modelingFamiliarity with cloud platforms (e.g., AWS, Azure, Google Cloud)Experience working with large-scale data systems (data warehouses, data lakes)Knowledge of A/B testing and experimentation frameworksKey SkillsData wrangling and cleaningStatistical analysis and modelingDashboard development and reportingBusiness intelligence and insight generationCritical thinking and problem solvingStakeholder communication and data storytellingTools & TechnologiesData querying: SQLProgramming: Python, RVisualization: Tableau, Power BISpreadsheets: Microsoft ExcelDatabases: SQL Server, PostgreSQL, MySQLOptional: Big data tools (Spark, Hadoop)Work EnvironmentOffice, hybrid, or remote analytics teamsCollaboration with business, product, and engineering departmentsFast-paced, data-driven decision-making environment