Staff Data Scientist, Applied Science

LinkedIn’s Data Science team leverages big data to develop data-driven solutions for LinkedIn’s Infrastructure organization. LinkedIn’s infrastructure is the backbone of our operations, encompassing data centers, servers, network infrastructure, power systems, and foundational software platforms that power all our products and services. A career at LinkedIn offers countless ways for an ambitious data scientist to have an impact.

This role involves guiding the Experimentation Platform team in developing a statistically correct, flexible, and powerful platform for online experimentation. You will be the statistical voice and technical lead, co-designing a new AI experimentation experience and backend, ensuring high-level functionality like hierarchical experimentation and statistical correctness guardrails. You will be in charge of developing and integrating a variety of experiment analysis techniques, including more powerful variance reduction methods, quantile treatment effect analysis, and cross-experiment analysis. Finally, you will help drive expansion of platform capabilities into additional experiment designs, such as cluster-randomized designs and budget split testing.

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

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.