AI Data & Analytics Engineer

DACUT Cannabis is seeking an AI Data & Analytics Engineer to deliver intelligent reporting, automation, and forecasting across a vertically integrated cannabis organization.

Responsibilities

• Develop and implement AI-powered tools to improve forecasting, reporting, operational efficiency, and financial decision-making
• Build machine-learning models for revenue forecasting, demand planning, inventory optimization, labor analysis, and expense management
• Find opportunities to automate recurring financial, operational, and executive reporting
• Develop AI-assisted workflows using large language models, APIs, and automation platforms
• Create systems to identify trends, anomalies, financial risks, and operational inefficiencies
• Evaluate emerging AI technologies and recommend practical applications across the organization
• Establish safeguards and validation processes to keep AI-generated insights accurate, secure, and reliable
• Analyze financial and operational performance: revenue, gross margin, operating expenses, labor costs, inventory value, profitability, and cash-flow trends
• Build financial models, forecasts, budgets, and scenario analyses for executive leadership
• Develop location-level, department-level, product-level, and brand-level profitability reporting
• Analyze performance across retail, cultivation, processing, distribution, and corporate operations
• Partner with Finance and Accounting to validate financial data and maintain consistent reporting standards
• Create automated reporting for actual performance versus budgets, forecasts, and prior periods
• Support strategic planning by identifying cost-saving opportunities, revenue trends, and performance risks
• Design, develop, and maintain executive-level Power BI dashboards and reporting tools
• Build scalable data models using Power Query, DAX, calculated measures, and relationships
• Create dashboards for financial performance, retail sales, inventory, cultivation yields, production output, labor, and operational KPIs
• Implement row-level security, scheduled refreshes, and data-quality controls
• Improve dashboard usability by presenting complex information in a clear and actionable format
• Establish consistent KPI definitions across departments and business entities
• Write, optimize, and maintain complex SQL queries, stored procedures, views, and data transformations
• Build and manage ETL/ELT pipelines to consolidate information from multiple systems
• Integrate data from POS, ERP, accounting, payroll, inventory, compliance, CRM, and operational platforms
• Create centralized datasets that support reporting, forecasting, and AI applications
• Monitor data pipelines, troubleshoot failures, and resolve inconsistencies between source systems
• Develop processes for data cleansing, validation, reconciliation, and documentation
• Support the development of a reliable data warehouse or centralized reporting environment
• Connect data across retail, cultivation, processing, distribution, inventory, finance, and corporate functions
• Develop reporting that tracks products and costs throughout the operational lifecycle
• Analyze cultivation yields, production costs, inventory movement, retail sell-through, product margins, and overall profitability
• Identify gaps between departments that impact data accuracy, inventory control, or financial performance
• Partner with leaders across each division to understand operational challenges and develop data-driven solutions
• Support standardized reporting across multiple locations, departments, brands, and legal entities
• Maintain accurate, consistent, and secure financial and operational data
• Develop documentation for data sources, models, calculations, dashboards, and automated processes
• Establish validation controls to identify missing, duplicated, or inaccurate information
• Protect confidential financial, employee, customer, and operational information
• Support reporting requirements within a highly regulated industry
• Ensure AI tools and data integrations follow company security, privacy, and compliance standards

Requirements

• Bachelor’s degree in Data Science, Computer Science, Data Analytics, Finance, Accounting, Engineering, or a related field
• 3 to 5 years of experience in data analytics, business intelligence, data engineering, financial analytics, or a related position
• Advanced SQL skills, including complex joins, CTEs, data transformations, query optimization, and database troubleshooting
• Advanced Power BI experience: dashboards, semantic models, Power Query transformations, and DAX calculations
• Demonstrated experience applying AI, machine learning, or predictive analytics to business problems
• Strong understanding of financial statements, budgeting, forecasting, profitability, and operational finance
• Experience integrating and reconciling data from multiple business systems
• Ability to translate complex technical findings into clear recommendations for executives and operational leaders
• Strong analytical, organizational, and problem-solving skills
• Ability to work onsite at the West Bloomfield corporate office

Technologies

• SQL
• Power BI
• Power Query
• DAX
• ETL/ELT
• APIs
• Large language models
• Machine learning

Preferred Qualifications

• Experience supporting a vertically integrated or multi-entity organization
• Experience within cannabis, manufacturing, retail, distribution, consumer packaged goods, or another highly regulated industry
• Experience with Python, Microsoft Fabric, Azure, Databricks, APIs, or cloud-based data platforms
• Experience building machine-learning models, AI agents, or large language model integrations
• Knowledge of ERP, POS, inventory-management, payroll, and accounting systems
• Experience analyzing product costing, inventory valuation, supply-chain performance, and multi-location profitability
• Familiarity with cannabis platforms such as METRC, Dutchie, Alpine IQ, or similar systems
• Experience developing enterprise data governance and KPI standardization

Role Outcomes

• Leadership has timely access to accurate financial and operational insights
• Manual reporting processes are replaced with reliable automated workflows
• Financial forecasts become more accurate and actionable
• Data from retail, cultivation, processing, inventory, and corporate systems is connected
• Power BI dashboards provide a consistent view of performance across the organization
• AI solutions deliver measurable improvements in efficiency, profitability, and decision-making

Location: West Bloomfield Township, MI (onsite)

Compensation: USD 90,000 - 110,000 per year