Software Engineer, Data Science

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.

Job Description

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 800 million 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 now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture. This person will work closely with cross-functional teams such as product, marketing, sales, engineering, and operations to develop infrastructure and deliver tools or data structures that enable data-driven decision-making.

Responsibilities

• Work with a team of high-performing data science professionals and cross-functional partners to identify business opportunities and build scalable data solutions.
• Build data expertise and manage complex data systems for a product or a group of products.
• Perform data transformations to serve products that empower data-driven decision making.
• Build and manage data pipelines; design and architect databases.
• Establish efficient design and programming patterns for engineers and non-technical partners.
• Design, implement, integrate, and document performant systems or components for data flows or applications that power analysis at massive scale.
• Share best practices and standards in our data ecosystem across teams.
• Translate analytical objectives into logical recommendations and drive informed actions.
• Partner with internal platform teams to prototype and validate in-house tools to derive insight from very large datasets or automate complex algorithms.
• Initiate and drive projects to completion with minimal guidance.
• Contribute to engineering innovations that fuel LinkedIn’s vision and mission.

Qualifications

Basic Qualifications

• Bachelor’s degree in a quantitative discipline (e.g., computer science, statistics, operations research, informatics, engineering, applied mathematics, economics).
• 2+ years of industry or academic experience working with large datasets.
• Experience with SQL and relational databases.
• Experience programming in at least one of: R, Python, Java, Scala, or PHP. (Rewritten to be measurable/objective.)

Preferred Qualifications

• MS or PhD in a quantitative discipline (e.g., statistics, operations research, computer science, informatics, engineering, applied mathematics, economics).
• Experience developing data pipelines using Spark and Hive.
• Experience with data modeling; ETL concepts; and patterns for efficient data governance, including manipulating massive-scale structured and unstructured data.
• Experience with distributed data systems such as Hadoop and related technologies (e.g., Spark, Presto, Pig, Hive).
• Experience in either data workflows/modeling, front-end engineering, or back-end engineering.
• Understanding of technical and functional designs for relational and MPP databases.
• Experience in data visualization and dashboard design using tools such as Tableau, R visualization packages, D3, or other JavaScript libraries.
• Knowledge of Unix or Unix-like systems, Git, and code review tools.

Suggested Skills

• Java
• Data Pipeline
• ETL
• Data Manipulation

You Will Benefit From Our Culture

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