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
Aptive Intelligent Pest Control™ is redefining the industry with a smarter, more proactive approach to pest control. By analyzing millions of pest data points across neighborhoods, pest activity, and weather patterns, Aptive tailors treatment plans to help homeowners stay one step ahead. We geek out so our customers don’t freak out. You never thought bugs could be this cool.
Our culture is built on accountability, discipline, and high integrity—we work hard and have fun doing it. Aptive has been recognized for both its impact and workplace culture, including Inc. Magazine’s Best in Business and Best of State, Glassdoor’s Top 100 U.S. Workplaces, and Entrepreneur Magazine’s Best Companies in America. And we’re just getting started.
To learn more, visit www.aptivepestcontrol.com or follow Aptive on Facebook (@AptivePestControl), Instagram (@Aptive.PestControl), and LinkedIn (@AptiveEnvironmental).
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please inform your recruiter.
