Senior Applied Scientist, Developer Productivity (DPX)

Company Description

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.

Job Description

LinkedIn's Data Science team leverages big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to drive member engagement, business growth, and monetization efforts. With over 1 billion members around the world, a focus on great user experience, and a mix of B2B and B2C programs, a career at LinkedIn offers countless ways for an ambitious data scientist to have an impact.

In this role within the Developer Enablement team in the DPX organization you will influence, transform, and create a great experience for our developers at LinkedIn through data and insights. We are a data-driven organization and you will be helping to lead critical efforts in gathering signals and providing insights to guide DPX's mission and strategic investments to make step function improvements in LinkedIn developer experience. You will be expected to apply your DS and ML expertise to develop strategies and guide solutions to establish the right telemetry for objective and subject signals from our engineering ecosystem comprising of key development machinery and the users themselves, gather the right data, and provide deep insightful analysis that can help direct and measure DPX's business impact on LinkedIn.

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

• Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities and develop algorithms and methodologies to address them.
• Analyze large-scale data from code, build, CI/CD, and developer tool usage to uncover patterns that impact productivity
• Conduct in-depth and rigorous data science research, model improvement, advanced experiments, observational causal studies to quantify the cause and effect in the ecosystem, identify business opportunities and to drive member value and customer success.
• Lead causal inference studies (observational, quasi-experimental, and novel methods) to quantify cause-and-effect in developer behavior and tooling, where traditional A/B testing is not feasible
• Apply and adapt cutting-edge research - e.g., causal inference techniques and large language models (LLMs) - to the developer productivity space, including fine-tuning existing models for code understanding or workflow optimization
• Collaborate with data scientists and software engineers to identify opportunities to improve developer productivity and design measurement methodologies tailored to engineering workflows
• Partner directly with software engineers to prototype, validate, and deploy solutions that make developers more effective in their daily work
• Promote adoption of new data science methods and elevate the practice of causal inference and machine learning across LinkedIn's developer ecosystem
• Translate insights into practical recommendations and tools that improve engineering velocity, reliability, and developer experience.
• 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
• Simplify and articulate complex technical findings to influence cross-functional partners like engineering leaders and senior executives
• Initiate and drive projects to completion independently
• Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews

Qualifications

Basic Qualifications

• Bachelor's Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.
• 3+ years of industry or relevant academia experience
• Background in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl)
• Experience in applied statistics and statistical modeling in at least one statistical software package, (eg. R, Python)

Preferred Qualifications

• BS and 5+ years of relevant work experience, MS and 3+