Data Scientist

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.

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 turns member and customer behavior into product decisions across one of the world's largest professional networks. We design experiments, investigate metric movements, and partner with PM and Engineering to ship features that create real economic opportunity for members, including the next generation of AI-powered experiences.

We're hiring an early-career data scientist to join a product team and grow under the mentorship of more senior Data Science ICs. You'll be responsible for writing SQL and Python to investigate how members use the product, read and interpret A/B test results, build dashboards and analysis docs that inform real decisions, and learn the craft of experimentation on data at LinkedIn's scale. You’ll deep dive into the tracking and algorithms of our AI stacks and learn how to use agentic data science to understand these systems and create insights that drive impact. As you grow, you'll take on more ambiguous problems and shape the metrics our team uses.

Responsibilities:

• Performs data-driven experiments and causal analyses to test and validate new product ideas or go-to-market strategies, develop ecosystem understanding, and monitor current products or systems.

• Performs analyses to support the definition of metrics that leads to data-driven target setting and decision-making.

• Leverage AI tools in day-to-day workflows to increase productivity

• Develops and employs models and causal analyses (e.g., panel analysis, A/B testing) to help determine what drives metric relationships and create actionable insights within basic product domains.

• Collaborates with relevant partners on defining metrics and frameworks for evaluating AI/LLM systems and agentic product performance.

• Supports AI system roadmaps through assessing model performance.

• Prototypes data solutions, and/or collaborates with relevant partners (e.g., Data Science teams, AI, Engineering) to operationalize, build, and validate scalable tools/applications/solutions for use by internal customers to convert data into insights at scale, with guidance.

• Embeds data science best practices and principles through all phases of development of customized and/or scalable data solutions.

• Provides consultation to partners on basic data questions to enable data democratization.

• Understands and identifies patterns of user behavior leveraging data mining techniques and provides insights and data-informed recommendations to internal partners.

• Creates compelling, data-centric stories based on analytical findings to support internal customers' decision-making.

Basic Qualifications:

• Bachelor's Degree in in Applied Mathematics, Computer Science, Data Science, Economics, Engineering, Informatics, Statistics, or related field

• 1+ year of experience in data science (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

• Background in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl)

Preferred Qualifications:

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

• Experience with experimentation platforms, causal inference, product domain expertise or evaluating AI / LLM-powered features.

• Written communication and structured thinking abilities

• Curiosity about how products work and why members behave the way they do

Suggested Skills

• Data Science

• Data Storytelling

• Statistics

• Strategic Thinking

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $101,000 to 167,000. 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.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a Reasonable Accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us and describe the specific Accommodation requested for a disability-related limitation.

Fill out an Accommodation request here: https://app.smartsheet.com/b/form/b660a0327d044969abfd7a4e73d15c36

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

• Documents in alternate formats or read aloud to you
• Having interviews in an accessible location
• Being accompanied by a service dog
• Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.

San Francisco Fair Chance Ordinance

Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

Pay Transparency Policy Statement

As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.

Global Data Privacy Notice and Compliance Posters for Job Candidates

Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.