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We are seeking a detail-oriented and analytical Data Analyst to transform Customer Service and operational raw data into actionable insights that support strategic decision-making across the organization and within Customer Service. In this role, you will work closely with cross-functional partners to interpret complex datasets, build reports, and develop scalable processes for ongoing analytics needs.
Job Responsibility:
Collect, clean, and validate large datasets from multiple internal and external sources
Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies
Build and maintain dashboards, visualizations, and reporting tools to support leadership and stakeholders
Translate data findings into clear, concise business insights that drive operational and strategic decisions
Partner with product, engineering, finance, and operations teams to understand analytical needs and provide data-driven recommendations
Perform ad-hoc analyses to support initiatives related to growth, product performance, and operational efficiency
Develop and maintain scalable data pipelines and automated reporting workflows
Ensure data accuracy, consistency, and integrity across systems
Identify opportunities to improve data collection and measurement frameworks
Present insights and recommendations to technical and non-technical audiences
Work closely with stakeholders to define metrics, KPIs, and reporting cadences
Document methodologies, data dictionaries, and analytics processes
Requirements:
Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field
3+ years of experience in data analysis or business analytics
Strong proficiency in SQL, including writing complex queries
Experience with data visualization tools (e.g., Tableau, Looker, Power BI, Mode)
Proficiency with Python or R for data manipulation and analysis
Strong analytical thinking, problem-solving, and attention to detail
Ability to communicate complex findings to wide-ranging audiences
Nice to have:
Experience working with large, complex datasets or cloud data warehouses (e.g., BigQuery, Snowflake, Redshift, DataBricks)
Familiarity with A/B testing methodologies
Knowledge of statistical modeling, forecasting, or machine learning concepts
Experience working in an e-commerce, marketplace, or tech environment
Experience working with customer service data
Data-driven mindset with excellent critical-thinking skills
Strong prioritization and project management abilities
Curiosity and eagerness to dig into data to uncover insights
Ability to work independently in a fast-paced environment