Hybrid Senior Data Science Engineer - Data Platforms & AI

Linkedin3; Mountain View (CA); Hybrid; USD 129,000 - 212,000; Full time

Job summary

LinkedIn is seeking a Sr Software Engineer, Data Science in Mountain View for building data applications, platforms, and AI-enabled data stacks. You will collaborate with data science, product, engineering, marketing, sales, and operations to translate business needs into reliable data products and scalable pipelines.

You will contribute to both application development and data engineering efforts, building self-serve tools and diagnostics, and ensuring data quality and usability for teams

Qualifications

• Bachelor's degree in a quantitative discipline (e.g., CS, Statistics, OR, Informatics, Engineering).
• 3+ years of relevant experience working with large data.
• Experience with SQL/Relational databases.
• Background in at least one programming language (e.g., R, Python, Java, Scala, PHP, JavaScript).

Responsibilities

• Designs and builds the architecture of both front-end and back-end for novel data applications.
• Develop and build methodologies, platforms, and tooling for experimentation and diagnostics.
• Designs, builds, and customizes reusable tools, dashboards, APIs, and integrations.
• Conceptualizes, defines, and socializes foundational metrics to scale with AI.
• Leverages AI-enabled data stack to accelerate discovery, design, development, testing, and maintenance.
• Communicates plans, progress, dependencies, and recommendations to cross-functional partners.
• Identifies gaps in data applications and proposes improvements to increase reuse and reliability.
• Applies data science and software engineering best practices across the lifecycle of data apps and pipelines.
• Support, monitor and improve operational excellence practices for data platforms.

Skills

SQL

Programming languages

Education

Bachelor's degree in a quantitative discipline

Master's degree (preferred)

Job description

LinkedIn is seeking a Sr Software Engineer, Data Science in Mountain View for building data applications, platforms, and AI-enabled data stacks. You will collaborate with data science, product, engineering, marketing, sales, and operations to translate business needs into reliable data products and scalable pipelines.

You will contribute to both application development and data engineering efforts, building self-serve tools and diagnostics, and ensuring data quality and usability for teams