Entry-Level Sales Data Analyst

Day-to-Day Responsibilities  

- Collect, cleanse, and validate daily, weekly, and monthly sales data sets.  

- Track key performance indicators (conversion rate, average deal size, pipeline velocity).  

- Generate concise dashboards in Power BI or Tableau for real-time monitoring.  

- Maintain and optimize the central sales database using Excel, SQL, and cloud warehousing tools.  

- Document emerging market trends, seasonality shifts, and regional anomalies.  

- Support quarterly and annual revenue forecasts with regression models and scenario analyses.  

- Collaborate with sales managers to refine targeting, discount tiers, and upsell tactics.  

- Champion data quality—design audits, reconcile discrepancies, and enforce naming conventions.  

- Present actionable insights in clear, persuasive language to non-technical stakeholders.  

- Continuously explore new analytics tools, APIs, and automation scripts to elevate efficiency.  

Must-Have Skills  

- Bachelor’s degree in Business Analytics, Economics, Computer Science, or related field.  

- Intermediate Excel (pivot tables, Power Query, nested formulas) and basic SQL experience.  

- Familiarity with at least one BI platform such as Looker, Tableau, or Power BI.  

- Solid grasp of statistical concepts: mean, variance, correlation, confidence intervals.  

- Excellent written and verbal communication; you transform dense tables into engaging stories.  

- Meticulous attention to detail—data integrity is never optional.  

- Adaptability; priorities shift fast in a sales environment.  

- Problem-solving mindset with the courage to challenge assumptions.  

Nice-to-Have Extras  

- Exposure to Python or R for data wrangling and visualization.  

- Experience with CRM systems (Salesforce, HubSpot) and their reporting modules.  

- Understanding of A/B testing frameworks and cohort analysis.  

- Knowledge of retail, fintech, or e-commerce sales cycles.  

- Certification in Google Analytics or similar platforms.  

Growth Opportunities  

- Rotate through cross-functional projects with marketing, product, and finance.  

- Access internal learning paths covering advanced SQL, machine learning, and storytelling.  

- Progress to Sales Analyst II or Revenue Operations Specialist within 18-24 months, based on impact.  

How We Work  

Our analytics team operates across time zones using agile rituals—stand-ups, sprint reviews, retrospectives. We prize psychological safety; every idea is welcome, every question valid. Performance is measured by insight quality, stakeholder satisfaction, and continuous improvement, not by seat time.