LinkedIn

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 Flagship Applied Science team is seeking a Senior Manager to lead a team of talented Applied Scientists focused on building cutting-edge inference, algorithms, and models that identify and quantify complex cause-and-effect relationships within our ecosystem. In this role, you will drive both the strategic direction and the day-to-day management of the team while directly contributing to LinkedIn’s Knowledge Marketplace strategy.

You will tackle unique and challenging problems, such as using causal inference techniques to quantify causality between input and outcome metrics, as well as measuring content creator and viewer network impact through experimentation. Your leadership will be essential in developing innovative, data-driven insights that shape our marketplace and advance LinkedIn’s position as a thought leader in this space.

Responsibilities:

• This role will include a mix of thought leadership, team management, and collaboration across other groups/functions (Product, AI, Engineering, etc.). The current scope will include a team of 8-10 direct reports.
• Provide direction and oversight for in-depth and rigorous causal analysis, development of causal methodology, and machine learning models to drive member value; design and conduct rigorous A/B tests, refine experimentation methodologies to identify and quantify complex cause and effect in the ecosystem and to continuously drive member values.
• Guide the team to explore vast datasets to discover relevant features and attributes that can improve the performance of existing models. Extract valuable information from unstructured data sources and apply feature engineering techniques to enhance model effectiveness.
• Continuously optimize and fine-tune models to meet business objectives and user expectations.
• Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights
• Promote and enable adoption of technical advances in Data Science; elevate the art of Data Science practice at LinkedIn.
• Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations and evangelize data-driven business decisions in support of strategic goals
• Partner with cross-functional teams to initiate, lead or contribute to large-scale/complex strategic projects for team, department, and company

Basic Qualifications:

7+ years of relevant work experience

Bachelor’s Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.

Experience with SQL or relational database query performance, and at least one programming language (e.g., R, Python)

Preferred Qualifications:

5+ years of management experience

10+ years of overall professional experience

Demonstrated thought leadership; experience publishing publicly visible research papers and/or speaking at conferences.

MS or PhD in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.

Suggested Skills

Leadership

Statistics - Statistical Modeling

Experimentation & Causal Inference

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 $191,000-$315,000. 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 at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.

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.

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 for Job Candidates

This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice