Key responsibilities include:
- Partner with teams across the company to understand their workflows, extract institutional and domain knowledge (data schemas, SQL queries, business logic), and reorganize it into a documented, AI-consumable knowledge base.
- Design and implement AI-driven solutions as ongoing, maintainable processes rather than one-off fixes — thinking in terms of systems that scale across the department.
- Evaluate and recommend AI tools and platforms, tracking new developments beyond mainstream tools (e.g., ChatGPT, Claude) and assessing their fit for CLIENT's needs.
- Mentor and train business users who have ideas but lack the technical skill to implement them — teaching best practices and running hands‑on sessions so teams can use AI tools independently.
- Analyze operational and business data to identify opportunities for automation, forecasting, and cost savings, ensuring the underlying variables and objectives are well understood before applying AI to a problem.
- Build and maintain reports and dashboards that track the performance and impact of AI-driven initiatives.
- Support presentations of findings and project updates to leadership.
- Support budget tracking, vendor coordination, and documentation for AI initiatives.
- Provide day-to-day guidance and oversight to the Analyst, AI Integration and Operations Efficiency, reviewing their work and helping develop their skills.
Education and experience:
- Bachelor's degree; business, finance, accounting, information systems, or computer science preferred. No AI-specific degree is expected — the field is new enough that hands‑on, self‑directed experience matters more than formal coursework.
- Minimum of two years of professional experience in data analysis, business analytics, AI/technology implementation, or a related field.
- Demonstrated, hands‑on AI experience beyond general chat use — e.g., working with AI coding tools, connectors, automations, or agentic workflows. A GitHub or portfolio of past work is a plus.
- Working knowledge of SQL and the ability to understand relationships between tables and data warehouse structure.
- Proficiency with data visualization tools (e.g., Power BI, Tableau); Python is a plus.
- Strong business acumen — able to understand what a process or metric is actually accomplishing, not only how to code it.
- Excellent interpersonal skills: able to build trust quickly with colleagues across departments, draw out how work really gets done, and explain technical concepts clearly to non-technical audiences.
- Comfortable presenting findings and recommendations to leadership.
- Experience in food service, logistics, distribution, finance, or procurement is preferred.
Essential skills & qualifications:
- Demonstrates strong independent analysis and critical thinking skills, applying sound judgment to solve problems and support business objectives.
- Brings expanded work experience and role‑specific education or expertise, along with intermediate to advanced proficiency in Microsoft Office and related systems.
- Effectively leads and contributes to discussions, articulating ideas and providing value‑driven insights relevant to their work and the organization.
- Shows initiative by proactively identifying opportunities, taking ownership of responsibilities, and seeking out additional tasks and challenges.
- Builds collaborative relationships by beginning to engage with a variety of stakeholders across teams and functions.
- Operates with a high level of accountability and reliability, requiring minimal supervision while consistently delivering quality results.
Desired skills:
- Experience implementing AI-driven forecasting or modeling that goes beyond static tools (e.g., building dynamic models with adjustable variables).
- Familiarity with process mapping, workflow documentation, and change management for new tools.
- Experience mentoring or training others, or leading workshops.
- Interest in AI ethics and responsible use of AI in business operations.