Data Analyst

Role: Data Analyst (Analytics & Insights)

We are looking for a sharp, curiosity-driven Data Analyst to join our Analytics team. You won't just be "pulling data"; you will be the bridge between raw numbers and strategic decisions.

In this role, you will own the full data lifecycle - from building automated pipelines and sleek visualizations to presenting high-stakes insights to our Product and leadership council. If you enjoy debunking myths with data and finding "the why" behind the "what," you'll fit right in.

Core Responsibilities:

• Metric & Dashboard Ownership: Design, develop, and maintain automated dashboards that serve as the "source of truth" for the business.
• Insight Generation: Go beyond the surface level. Analyze trends and anomalies to provide actionable recommendations that drive growth.
• Stakeholder Communication: Lead the weekly Analytics Council reviews, translating complex technical findings into clear, executive-level narratives.
• Experimentation (A/B Testing): Design experiment frameworks, calculate sample sizes, and perform post-hoc analysis to determine the success of product or marketing changes.
• Ad-hoc Analysis: Support rapid-fire business questions with deep-dive investigations to support urgent decision-making.
• Automation & Efficiency: Identify repetitive manual reporting tasks and build scripts or workflows to automate them, freeing up time for high-value analysis.
• Innovation & Process Improvement: Constantly evaluate our data stack and methodologies. Propose new tools, statistical models, or data collection techniques to keep us ahead of the curve.

Technical Requirements
- Data Querying: Advanced SQL (Window functions, CTEs, Query optimization)

- Visualization: Proficiency in Tableau, Power BI, or Looker

- Programming: Python or R (specifically for data manipulation and automation)

- Experimentation: Understanding of hypothesis testing, p-values, and confidence intervals

- Data Cleaning: Experience with ETL/ELT processes and data warehousing (e.g., Snowflake, BigQuery)

What Makes You a Great Fit

• The "So What?" Factor: You don't just report that a metric moved; you explain why it moved and what the business should do about it.
• Precision: You have a high bar for data integrity. You'd rather double-check a join than present a wrong number.
• Adaptability: You thrive in a fast-paced environment where priorities can shift based on new data.
• Storytelling: You can take a messy spreadsheet and turn it into a compelling 3-slide deck for executives.

Qualifications

• Experience: 2.5 years in an analytical role (Product, Marketing, or Business Analytics).
• Education: Bachelor's or Master's degree in a quantitative field (Statistics, Computer Science, Economics, Engineering, etc.).
• Communication: Proven experience presenting to senior leadership or cross-functional stakeholders.