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.
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 globally, and a mix of B2B and B2C programs, we offer countless ways for ambitious individuals to have an impact and transform their careers. We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture.
The Data Science Technical Foundation team is an engineering team embedded into data science groups in charge of developing robust data applications and data tooling to empower the rest of the data science team and cross functional teams. This individual will work closely with data science partners and other cross-functional stakeholders, including AI, Product Managers, and Engineering, to tackle a variety of projects. These projects may range from building 0-1 data applications or enhancing core data science tools to streamline complex analyses or develop new methodologies. This role is unique in that it allows you to work end-to-end on new initiatives and build data solutions from the ground up.
The Flagship Data Science Tech Foundation team builds data applications that drive innovation and productivity. Our work provides a rigorous engineering foundation for novel, state of the art data science methodologies and amplifies their impact through increased scalability, availability and iterative velocity. We own diagnostic platforms that query data from various microservices, data stores and process them in online and nearline fashion to generate insights behind our AI systems. In addition to generating system insights, we also own the platform that provides causal inference capabilities to the entire Data Science organization, generating conversion factors between various metrics and their respective proxies.
Responsibilities:
Work with a team of high-performing data science professionals, and cross-functional teams to identify business opportunities and build scalable data solutions and applications.
Establish efficient design and programming patterns for engineers as well as for non-technical partners.
Build web applications and platforms that enable producers and consumers of data insights to work smarter and more efficiently.
Lead the architecture and design of both front-end and back-end for novel data applications.
Own the application development for one or more of our internal products and collaborate with other engineers, data scientists, and product managers to launch new products, iterate on existing features, and build a world-class user experience.
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.
Basic Qualifications:
Bachelor's degree in Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics or a related field, or equivalent experience.
5+ years of industry experience
Background in at least one programming language (e.g., R, Python, Java, Scala, PHP, JavaScript, prefer Python, Java and Scala).
Preferred Qualifications:
BS and 7+ years of relevant work experience, MS and 5+ years of relevant work experience, or Ph.D. and 3+ years of relevant work/academia experience working with large amounts of data.
Experience writing RESTful APIs / gRPC with modern frameworks.
Experience with data products and basic statistics.
Experience with SQL/Relational databases.
Experience working with data pipeline authoring system, such as Airflow, Flyte, DBT
Experience creating data visualizations and UX design
Experience building data science or machine learning platforms.
Familiarity with source control, testing frameworks, and all aspects of developing in large, distributed software teams.
Excellent communication skills, with the ability to synthesize, simplify and explain complex problems to different types of audiences.
Suggested Skills :
Spring/Flask
Data Visualization
UX Designs
Technical Leadership
Web App Development using React.js
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 $147,000 to $240,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. The total compensation package for this position may also include annual performance bonus, stock and benefits. For additional information, visit:
Equal Opportunity Statement
LinkedIn is committed to diversity in its workforce and is 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 an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: :b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C QxVTbg?e=5hfhpE. Please reference and for more information.
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Date Posted: 13 April 2025
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