Staff Software Engineer, Data Science

LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology.

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.

About the team:
LinkedIn’s Trust \ team's goal is to leverage big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to create a Trusted and Safe Platform, drive member engagement, business growth and monetization . 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.

The Trust Data Science team delivers data & metrics insights, develops data platforms / tools and enables decisions at scale through inference and algorithm as part of the cross-functional Trust team to realize its mission to create safe, trusted, professional experiences where individuals and organizations can be productive and successful. In this role we are looking for a technical leader in the Trust Data Engineering and Platform team. This person will work closely with various cross-functional teams such as product, engineering, and operations to develop infrastructure and deliver tools or data structures that enable data-driven decision-making. Successful candidates will exhibit technical acumen and business savviness with a passion for making an impact by enabling both producers and consumers of data insight to work smarter.

Responsibilities

• Work with a team of high-performing data science professionals, and cross-functional teams to identify business opportunities and build scalable data solutions.
• Build data expertise, act like an owner for the company and manage complex data systems for a product or a group of products.
• Perform all of the necessary data transformations to serve products that empower data-driven decision making.
• Establish efficient design and programming patterns for engineers as well as for non-technical partners.
• Design, implement, integrate and document performant systems or components for data flows or applications that power analysis at a massive scale.
• Ensure best practices and standards in our data ecosystem are shared across teams.
• Understand the analytical objectives to make logical recommendations and drive informed actions.
• Engage with internal data platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms.
• Contribute to engineering innovations that fuel LinkedIn’s vision and mission.
• Be a thought leader and modernize the data stack used by the team.