Linkedin Data Analyst Jobs in California (NOW HIRING)

LinkedIn is the world's 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. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun - where everyone can succeed.

This role will be based in Mountain View, CA.

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.

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, LinkedIn offers countless ways for an ambitious data engineer to have an impact and transform your career. 

We are looking for a talented and driven Sr Software Engineer, Data Science to help build data applications, platforms, and engineering foundations that enable LinkedIn's Data Science organization to move faster and make better decisions. In this role, you will work closely with data science, product, engineering, marketing, sales, and operations partners to translate business and analytical needs into reliable data products, reusable tools, and scalable data systems. You will contribute to both application development and data engineering efforts, including building self-serve tools, diagnostic workflows, data pipelines, curated datasets, metrics foundations, and integrations with LinkedIn's AI-powered data stack. Successful candidates will bring strong SQL and programming skills, practical software engineering judgment, and a passion for creating dependable data products that improve how teams discover, understand, and act on data. 

Responsibilities: 

 Designs and builds the architecture of both front-end and back-end for novel data applications aligned to open-ended or complex business problems/opportunities. 

 Develop and build methodologies, platforms, and tooling that support experimentation, causal inference, measurement, and diagnostics for complex product and business questions 

 Designs, builds, and customizes reusable tools, frameworks, dashboards, APIs, and integrations that make data applications and engineering solutions easier to adopt, operate, and extend across teams. 

 Conceptualizes, defines, and socializes foundational metrics to set organizational goals and scale with AI to democratize data-driven decision-making. 

 Leverages LinkedIn's AI-enabled data stack and AI tools to accelerate discovery, design, development, testing, documentation, maintenance, and iteration of data products, applications, and pipelines. 

 Uses domain knowledge to evaluate design tradeoffs, identify risks, and communicate technical plans, progress, dependencies, and recommendations to cross-functional partners so data applications, pipelines, and tooling remain useful, reliable, and aligned to business needs. 

 Identifies gaps in existing data applications, tools, workflows, datasets, and pipelines, then proposes and implements improvements that reduce manual work, improve reliability, and increase reuse across projects. 

 Applies data science and software engineering best practices across the lifecycle of data applications and data engineering solutions and participates in code, data model, pipeline, and design reviews, providing constructive feedback and technical guidance to peers that improves maintainability, scalability, data quality, and user experience. 

 Support, monitor and continuously improve operational excellence practices for data applications and platforms, including reliability, observability, incident response, scalability, privacy, and production readiness.

Basic Qualifications:

    Bachelor's Degree in a quantitative discipline: Computer science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, etc.

    3+ years of relevant industry or relevant academia experience working with large amounts of data

    Experience with SQL/Relational databases

    Background in at least one programming languages (e.g., R, Python, Java, Scala, PHP, JavaScript)

Preferred Qualifications 

• Master's Degree in Computer Science, Data Science, Software Engineering, Statistics, Applied Mathematics, or related field. 

Suggested Skills:

    Communication

    Decision Making

    Data Science

    Domain Knowledge and Skills

    Strategic Thinking

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $129,000 to $212,000. 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.

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