Job summary
A healthcare-focused company is seeking a Staff Data Scientist with over 7 years of experience to support the adoption of agentic AI and optimization algorithms within their platform. This role involves applying machine learning techniques and AI-driven workflows to solve complex business problems and enhance operational efficiency. The position requires strong collaboration with engineering, product management, and operations teams, emphasizing production-level Python development and measurable business impact.
Location and work setup
- Location
- Tromsø
- Work setup
- Remote
Salary
USD 194400.00–216000.00 year
Responsibilities
Leverage data analytics to address diverse business challenges using appropriate technical tools. Collaborate with cross-functional teams to define and execute strategies. Design frameworks and metrics to monitor data product performance and business outcomes. Investigate operational challenges to propose practical solutions. Lead the development and assessment of predictive and descriptive models. Promote and implement workflows powered by large language models (LLMs), partnering with engineering to build scalable and production-ready AI agent systems integrated into core products and tools fostering developer productivity.
Qualifications
Minimum 7 years of professional experience with complex business problem-solving and maintaining production Python code. Strong foundation in traditional predictive machine learning approaches and the ability to discern usage of advanced models such as LLMs. Deep specialization in either optimization algorithms (e.g., linear/integer programming for logistical and allocation challenges) or agentic AI (developing autonomous decision-making systems using LLMs). Proficient in setting success metrics aligned with business objectives, with a quantitative background in relevant fields or equivalent experience. Demonstrated ability to navigate ambiguity, communicate complex technical concepts clearly to diverse stakeholders, and take accountability across project lifecycles. Bonus skills include experience in experimental design with causal inference, marketplace optimization, modern MLOps practices, cloud infrastructure, and working with sensitive data under compliance regulations.