LinkedIn is the world’s largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters.

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


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+ years of relevant work experience, or Ph.D. and 1+ years of relevant work/academia experience
• MS or PhD in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.
• Demonstrated track record of developing or adapting causal inference methods for complex, non-experimental data.
• Exposure to LLM applications (fine-tuning, evaluation, or workflow integration) with an interest in applying them to improve how developers work
• Strong passion for transforming developer productivity and reshaping how software engineering is done in the new era

Suggested Skills
• Machine Learning
• Research
• Causal Inference

You will Benefit from our Culture:
We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $139,000.00 to $229,000.00 Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.


Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

-Documents in alternate formats or read aloud to you
-Having interviews in an accessible location
-Being accompanied by a service dog
-Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

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