We’re looking for a Senior Applied Scientist and a proven leader passionate about leveraging the latest AI techniques to build customer-facing product features that solve complex operations challenges. We expect you to collaborate with product managers, ML engineers and development teams to drive alignment on ML/AI-driven features at PagerDuty and deliver impact to our customers. If you are technical, creative, team-oriented, and excited about fostering an environment amongst our engineers that helps create avenues for success and learning, then this is an excellent opportunity for you.
**PagerDuty is a flexible, hybrid workplace. We embrace and encourage in-person working as an integral part of our culture. Both our employees and external research tells us that co-located collaboration strengthens connections, drives innovation, and accelerates learning.
This role is expected to come into our Lisbon office 1 day per month, so you can thrive in your new role and fully embrace being a Dutonian!**
Key Responsibilities:
- Build production-grade ML models and AI-powered solutions to business critical challenges across multiple domains on top of PagerDuty’s data infrastructure.
- Work both independently and collaboratively with other applied scientists, product managers, engineers, and designers to solve complex problems that deliver business value.
- Influence leadership and stakeholders to drive more data-informed decisions and to identify impactful AI use-cases across our products.
- Communicate, align and drive interest within the entire organization to be more data driven.
- Provide guidance, enablement, technical leadership, and mentorship to other members of the organization.
- Lead research initiatives using generative AI, agents and traditional ML techniques
- Proactively recommend improvements and new approaches to ensure continuous improvement across our existing models and services and tackling technical debt.
Minimum Requirements:
- Graduate degree in computer science, statistics, mathematics, or related quantitative field.
- You have 7+ years using machine learning and statistical analysis for building data-driven product solutions for large scale systems.
- Hands on experience in python, SQL and other related tools
- Have an entrepreneurial mindset to drive research projects to completion with minimal guidance.
- Strong ability to justify technical prioritization and communicate scientific work in a clear and effective manner stakeholders, other engineers and Product
- Experience working with Engineering teams ensuring a timely delivery
Preferred Requirements:
- Desire to keep learning new concepts and adapting to the start-of-the-art
- Experience shipping reliable and scalable AI/ML products and monitoring usage/performance/impact
- Prior experience in a SaaS environment
- Experience converting research work and POC’s into new customer-facing products and features
- Prior record of published work in technical forums, contributions to open source projects, or research innovations.
