Data Analyst

Profile: Junior Data Analyst

Key Responsibilities

• Collect, clean, and organize data from multiple sources (databases, spreadsheets, logs, APIs)
• Perform exploratory data analysis to identify trends, patterns, and anomalies
• Build and maintain dashboards and reports for technical and non-technical stakeholders
• Write SQL queries to extract and aggregate data for analysis
• Support ad-hoc data requests from product, business, and leadership teams
• Document data definitions, assumptions, and analysis methodology
• Validate data quality and flag inconsistencies or errors
• Collaborate with data engineering and data science teams on data pipeline needs
• Present findings clearly to both technical and non-technical audiences

Requirements & Tech Stack

• SQL: comfortable writing queries, including joins, aggregations, filtering, and subqueries
• Excel/Google Sheets: pivot tables, formulas, data cleaning
• Python or R basics: pandas/NumPy (or equivalent) for data manipulation
• Data visualization: Power BI, Tableau, or similar (or strong Excel/Sheets charting)
• Basic statistics: mean/median/variance, distributions, correlation, hypothesis testing fundamentals

Qualifications

• 0–2 yrs experience in data analysis, analytics, or a related role (internships count)
• Strong attention to detail and data accuracy
• Clear written and verbal communication skills
• Willingness to learn and adopt AI tools within an advanced, AI native work ecosystem, including comfort using AI assisted tools

What We Expect

• Ask good questions before diving into analysis; understand the "why" behind a request
• Double check your own numbers before sharing results
• Be curious and proactive in spotting data quality issues
• Take feedback well and iterate quickly
• Stay curious about AI native tools and workflows, and actively build fluency in using them for analysis and productivity
• Grow into more independent, complex analytical work over time