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Senior Economist, AI/ML

LinkedIn

LinkedIn

Software Engineering, Data Science
Sunnyvale, CA, USA
Posted on Thursday, June 13, 2024
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.

This role will be based in Sunnyvale, Bellevue, or New York City.

At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.

The candidate will work in collaboration with machine learning scientists, data scientists, and engineers by bringing knowledge and tools from Economics to help LinkedIn solve its core business and AI problems. The scope ranges from solving complex marketplace design questions to developing empirical solutions that integrate causal inference into machine learning. The candidate will combine theory and empirics to design, prototype, implement (in collaboration with engineers), and evaluate new ideas through experimentation. This is an applied role, directed towards making a positive and measurable impact on the LinkedIn product and its users.

To achieve this, the candidate will engage with a variety of other roles across LinkedIn (Data Science, Product Management, Business Operations, Engineering, and other teams and colleagues within AI). The candidate is expected to share findings and advocate for new methodologies via internal presentations and documentation across business lines. Research ideas are a natural byproduct of the role, and the candidate will be encouraged to present work at external academic forums via publications.

Responsibilities:
• Work with a team of high-performing data science professionals, machine learning engineers and cross-functional teams to identify business opportunities and develop algorithms and methodologies to address them.
• Design and build market mechanisms to improve auction efficiency, matching quality, and drive business growth.
• Analyze large-scale structured and unstructured data.
• Conduct in-depth and rigorous data science research, model improvement, advanced experiments, observational causal studies to quantify the cause and effect in the ecosystem, identify business opportunities and to drive member value and customer success.
• Develop methodologies to enhance LinkedIn’s product and platform capabilities.
• 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.
• Improve LinkedIn’s ability to measure and credibly speak to labor market trends and other economic phenomena.
• Initiate and drive projects to completion independently
• 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
• Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews

Basic Qualifications:
• PhD in Economics or closely related field (Finance, Quantitative Marketing, Statistics)
• Track record of research (working papers, publications, or participation in conferences or workshops)
• Demonstrated experience in machine learning
• Working knowledge of Python or R and their data science ecosystem

Preferred Qualifications:
• Experience working as an economist alongside or embedded in engineering roles (machine learning engineers, data scientists).
• Experience working with large scale online marketplace or matching systems
• Research experience in auction design, matching algorithms, industrial organization
• Interest in combining causal inference and econometrics with machine learning (estimation of heterogeneous treatment effects through e.g. causal trees/forests; double/debiased ML; causal reinforcement learning; etc.). Experience with related tools (EconML, CausalML) and/or research projects in these areas are an added plus.
• Advanced knowledge of experimental design including setup of RCTs (A/B tests) in presence of marketplace or network effects.
• Exposure to software engineering: big data technologies (Hadoop, Hive, Presto or other SQL engines, Spark) and software development best practices (code reviews, version control, modular design, unit testing).

Suggested Skills
• Market Design
• Economics
• Causal inference
• Machine Learning
• Methodology Research

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $128,000 to $210,000. 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
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: https://microsoft.sharepoint.com/:b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C_QxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.

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.

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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