Staff Data Scientist, Applied Science

Responsibilities

• Co-design the new AI experimentation experience and the backend that powers it.
• Collaborate cross-functionally to identify business opportunities and develop algorithms and methodologies to address them.
• Analyze large-scale structured and unstructured data.
• Develop methodologies to enhance LinkedIn’s online experimentation capabilities.
• Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights.
• Promote and enable adoption of technical advances in Data Science; elevate the art of Data Science practice at LinkedIn.
• Initiate and drive projects to completion independently.
• Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations and evangelize data-driven business decisions in support of strategic goals.
• Partner with cross-functional teams to initiate, lead or contribute to large-scale/complex strategic projects for team, department, and company.
• Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews.

Basic Qualifications

• MS or PhD in a quantitative discipline: Statistics, Economics, Applied Mathematics, Operations Research, Computer Science, Informatics, or other quantitative field relevant to the science of experimentation.
• Expertise in statistics, including analysis of bias and variance for experimental design and analysis approaches.
• Fluent in at least one programming language and a capable user of AI software engineering tools.
• Ability to establish requirements and design a new system for a broad set of users.
• 3+ years in a position that includes substantial technical leadership. 10+ years of total experience

Preferred Qualifications

• Experience in infrastructure/platform development.
• Ability to collaborate with and shape technical solutions for a broad set of customers and stakeholders.

Suggested Skills

• Structured thinking around bias
• Understanding of AI Experimentation
• Leadership

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