Data Analyst

Role Overview

• Conduct custom analysis of POS and retail sales data for manufacturer clients, delivering insights that support strategic decisions around pricing, assortment, and market share
• Partner directly with clients to scope analytical requests—ask sharp questions, define the right approach, and manage expectations throughout the project lifecycle
• Translate client business problems into research frameworks and produce polished, executive-ready deliverables including deep-dive reports and PowerPoint presentations for merchant meetings, QBRs, and product line reviews
• Write and refine SQL queries and Python scripts against our ClickHouse data warehouse to extract, transform, and analyze large-scale retail datasets
• Help design the frameworks, templates, and operational processes the research team will use as we scale
• Partner cross-functionally with marketing to provide data-backed insights for content creation and thought leadership
• Serve as a primary power user of Bolt—testing its capabilities against real client needs and pushing it to automate an increasing share of recurring analytical workflows
• Provide structured, actionable feedback to the Bolt development team based on day-to-day client work, helping prioritize features and surface gaps in platform coverage
• Apply your analytical expertise to develop reusable patterns, templates, and evaluation cases that improve Bolt's accuracy and coverage
• Help evaluate Bolt's analytical outputs for accuracy and relevance, contributing to quality benchmarks grounded in real-world use cases

Requirements

• At least 2 years of professional experience in a research, data analysis, or insights-driven role
• Experience analyzing POS, retail sales, or similar transactional data in a professional setting
• Strong SQL skills—you can write complex queries involving window functions, CTEs, joins across large tables, and aggregations with confidence
• Proficiency in Python for data analysis, scripting, and automation
• Expert-level skills in Excel and PowerPoint; ability to take raw data and turn it into a clear, compelling story for a non-technical audience
• Client-facing communication skills—comfortable leading calls, asking probing questions, and managing stakeholder expectations
• Experience with Git and GitHub-based development workflows
• Self-starter mentality—you move fast, stay motivated, and take ownership without needing to be micromanaged
• Startup agility—comfortable with ambiguity and wearing multiple hats in a fast-paced environment

Tech Stack

• Python
• SQL

Benefits

• Impact at Scale: Influence a $2.3 trillion industry by shaping how data science accelerates ROI for major manufacturers.
• Autonomy & Growth: Enjoy the freedom to experiment with new technologies and see your ideas realized in production.
• Collaborative Culture: Work alongside a supportive team that values positivity, proactive ownership, and continuous learning.
• Professional Development: Work with the latest technology in the AI stack