Director, Artificial Intelligence

We are seeking a hard-working, innovative, detail-oriented and creative team player to join our Aptive team! This is a full-time Director, Artificial Intelligence position located in Provo, Utah. Aptive has grown from a 2015 startup into one of the fastest-growing pest control companies in the US, serving 76 markets with 2,600+ employees. Our Pest Intelligence Center already blends AI, technician field observations, customer service data, and environmental modeling to forecast pest activity — and we're looking for the leader who takes that from a promising capability to a durable competitive advantage.

This is a new role and a builder's role. You'll define Aptive's AI strategy and then personally help ship it: models that decide how we route technicians, when we treat a property, which customers are at risk, and how our service teams spend their time. Success is measured in operational outcomes — retention, route density, first-time resolution — not in papers or proofs of concept.

What we offer:

• $200k Salary
• Annual Merit bonus of up to 20%
• Group Health, Dental, and Vision plans
• Pet insurance, Life insurance, and EAP benefits
• 401K with employer match up to 4%
• Paid holidays and paid time off
• Opportunity for advancement
• Upbeat and exciting company culture and much more!

Responsibilities include:

• AI strategy and roadmap for the Technology organization, prioritized by business impact and sequenced against real data and platform readiness
• The Pest Intelligence Center — evolving pest activity forecasting into proactive service planning across all markets
• Applied ML in production: demand and pest-pressure forecasting, route and scheduling optimization, churn and retention modeling, dynamic pricing inputs, and lead qualification for our sales channels
• Customer and technician-facing AI: contact center automation, agent assist, and decision support in the technician mobile experience
• Team building — hiring and growing a team of ML and data scientists, and setting the standards, tooling, and review practices they work to
• Partnership with Data Engineering on the warehouse and feature infrastructure these models depend on
• AI governance: model monitoring, drift detection, bias review, data privacy, and a clear position on responsible use of customer data

What the first year looks like

• Days 1–90: Audit existing AI and data assets, including the Pest Intelligence Center. Deliver a prioritized roadmap with named business owners and defined success metrics

• Months 3–6: Ship or measurably improve two production models tied to P&L outcomes. Stand up model monitoring and a deployment path

• Months 6–12: Hire the core team. Establish the intake process by which the business requests AI work, and demonstrate compounding returns on at least one flagship initiative
  

Requirements:

• 8+ years in data science, machine learning, or AI, including 3+ years leading teams
• A track record of ML systems in production that changed a business metric — you can explain the metric, the lift, and how you measured it
• Depth in forecasting, optimization, or recommendation systems
• Strong Python and SQL; fluency with a modern cloud data stack (we run Snowflake)
• Experience with LLM-based applications, and the judgment to know when they're the wrong tool
• Ability to translate between executives and engineers, and to say no to low-value AI requests
• Hands-on enough to review a colleague's model and debug a pipeline

Nice to have:

• Field service, logistics, home services, route-based operations, or seasonal-demand businesses

• Geospatial or environmental modeling

• Built a data science function from scratch at a mid-size company

• MS or PhD in a quantitative field