About the Company
Hoodie Analytics supports cannabis brands, consumers, and retailers with a comprehensive suite of analytics, apps, and data-enabled services that provide marketplace intelligence on sales, distribution, price, and promotion. Data is at the core of our business; we maintain the largest database of cannabis activity, held to the highest standards of quality and accuracy.
About the Role
We are looking for a hands-on Lead Catalog Analyst to lead our Catalog team of junior analysts. This is a player-coach role with three equally important dimensions: you will carry your own analyst workload, manage the team operationally, and serve as the team's AI workflow owner — identifying where AI agents and automation can improve how we work, building those workflows, and driving adoption across the team.
You will work closely with the Catalog Technical Lead, who serves as the bridge between the Catalog team and Data Engineering, to translate your operational observations into actionable requirements for tooling and workflow improvements.
On the AI side, you will own the process of designing and deploying low-code/no-code agents that reduce manual effort, improve consistency, and free your analysts to focus on higher-value work. You will lead by example here, modeling AI-forward ways of working and building a culture where the team is continuously looking for opportunities to work smarter.
Primary Responsibilities
AI Workflow Ownership & Agent Development
- Identify manual, repetitive, or error-prone processes in catalog operations where AI agents can meaningfully improve speed, consistency, or quality
- Design, build, and iterate on AI-powered workflows using low-code/no-code tools, You don't need to write code, but you need to be able to get your hands in the tools and make things work
- Prompt-engineer and configure agents for catalog-specific tasks such as product categorization, data enrichment, anomaly flagging, and quality review
- Drive adoption of AI tools across the team — train analysts, document workflows, and create feedback loops that improve agent performance over time
- Partner with the Catalog Technical Lead to escalate agent workflows that require deeper engineering support or integration into existing data infrastructure
- Stay current with the evolving AI tooling landscape and bring forward-looking recommendations on what the team should be experimenting with next
Team Leadership & Coaching
- Manage a team of junior catalog analysts: set clear performance objectives, monitor daily work output, and provide regular coaching and developmental feedback
- Foster a culture of accuracy, consistency, and continuous improvement, including a bias toward using AI tools to work more effectively
- Onboard new analysts and maintain training materials that reflect current tools, AI workflows, and best practices
Quality, Performance & Process
- Define and implement KPIs for catalog team output, such as accuracy rates, throughput, error rates, and enrichment completeness
- Build and maintain reports and dashboards that give the team and company visibility into data quality across dispensary and product work
- Identify operational inefficiencies and communicate them clearly to the Catalog Technical Lead — you define the 'what and why,' the Technical Lead handles the 'how'
- Document team workflows and best practices, keeping them current as processes and tooling evolve
- Present team performance results and process improvement proposals to internal stakeholders; receive feedback with openness and flexibility
Individual Contributor Work
- Maintain your own active portfolio of dispensary and/or brand catalog work at a high level of accuracy and enrichment
- Model the quality standards and attention to detail you expect from the team
- Stay current with cannabis product categories, market trends, and data sources relevant to catalog quality
Qualifications
Must-Have Skills
- 6-10 years experience in data analysis
- 2-5 years managing a team
- Prior experience in the cannabis industry, especially with product knowledge and familiarity with product categories
- Demonstrated experience cleaning, standardizing, and QA-ing large datasets: able to spot patterns and inefficiencies quickly
- Strong Excel and Google Sheets skills
- Proficient in SQL: comfortable querying data to audit quality and investigate discrepancies (you don't need to build pipelines, but you need to pull and interpret data)
- Experience using internal tools and dashboards to monitor team output and data quality; able to learn new tools quickly
- Advanced written and verbal communication skills: able to clearly document processes, write requirements, and present findings to non-technical stakeholders
- High attention to detail combined with an operational mindset: you can zoom in on a data problem and zoom out to see how it affects the broader workflow
- Prior people management or mentorship experience
Nice-to-Have Skills
- Experience working with product or inventory data in a retail, wholesale, or SaaS environment
- Familiarity with data flow diagrams or basic Python (ability to read, not necessarily write)
- Background in data quality governance frameworks or documentation
- Experience collaborating with data engineering or product teams on workflow tooling
Compensation package
What We Offer
- Comprehensive benefits package including 401k, health, and dental insurance
- Flexible work arrangements
- A collaborative, innovative work environment that values professional growth
- Opportunities to work on cutting-edge technologies and products that make a difference in the cannabis industry
Equal Opportunity Statement
We are committed to diversity and inclusivity.
