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Datavations

AI Data Analyst

Posted 6 Days Ago
Remote
Hiring Remotely in USA
95K-110K Annually
Junior
Remote
Hiring Remotely in USA
95K-110K Annually
Junior
Conduct client-facing analysis of POS and retail sales data to produce strategic insights. Scope research, write SQL and Python scripts to extract and analyze large datasets, create executive-ready deliverables, and serve as a power user of Bolt to improve and evaluate AI-driven analytics. Partner cross-functionally and manage client expectations throughout projects.
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Data Analyst At Datavations 

About Datavations

Datavations is the leading provider of SKU and store-level point-of-sale data for the home improvement retail industry. We serve manufacturers who sell through Home Depot, Lowe's, Menards, and other major retailers, delivering the data intelligence they need to win at the shelf. We are building Bolt, an AI-powered analytics platform that transforms how clients interact with their data—moving from manual analysis toward conversational, self-service intelligence.

About the Role

This hybrid role blends rigorous client-facing research with AI-assisted analysis. Your primary focus is delivering high-quality insights to manufacturer clients using POS and retail sales data - and, increasingly, leveraging Bolt, our AI-powered analytics platform, to do that work faster and at greater scale. 

You will bridge the gap between complex data and actionable strategy. You will scope research projects, manage client relationships, and translate raw POS and retail sales data into compelling narratives for merchant meetings, product line reviews, and quarterly business reviews. You will work closely with the dedicated Bolt development team - sharing structured feedback from the front lines of client work that directly shapes how the platform evolves. 

The ideal candidate is emerged by AI tools, eager to push the boundaries of what automated analysis can deliver, and sharp enough to know when a client situation demands the kind of human judgement and expertise no platform can replicate.

What You’ll Do

Client-Facing Research & Analytics

  • 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

AI Platform Development

  • 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


Who You Are

Required

  • 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

Preferred

  • Experience with AI coding tools, particularly Claude Code or similar LLM-assisted development workflows
  • Familiarity with LLM application development (prompt engineering, tool-calling patterns, evaluation frameworks)
  • Experience with ClickHouse or other columnar / analytical databases
  • Background in the home improvement, retail, or CPG industries
  • Experience building or contributing to data products or internal analytics platforms

Why Join Us

  • 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

Compensation 

The base salary average range for this role is $95,000 - $110,000 depending on experience, skills, and alignment with the role’s responsibilities. This range reflects our current national expectations for qualified candidates. Exceptional candidates based in our NYC office may be considered for a higher range. Total compensation may also include equity, performance bonuses, and a comprehensive benefits package.

We’re committed to paying competitively and equitably, and we regularly review our compensation structures to ensure they align with the market and support our values


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