Business Operations, Senior Associate - Consumer BI & Analytics

Company Description

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.

Join us to transform the way the world works.

Job Description

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. 

This role will be based in San Francisco, Mountain View, or Sunnyvale

This role will be part of Business Operations within Product Ecosystem Performance and Strategy team. The team combines deep business understanding with business intelligence and advance analytics capabilities. We enable our business partners across Product and Engineering to make informed decisions, manage risks, and identify opportunities across multiple business areas. 

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.

Qualifications

Basic Qualifications:

• Bachelor's Degree in a quantitative discipline: Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, or relevant work experience 
• 4+ years of experience in the technology industry, or relevant academia experience working with large amounts of data
• 4+ years of programming experience in R, Python, Java, or Scala
• 2+ years of experience with SQL / Relational databases

Preferred Qualifications:

• MS or PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
• Experience with distributed data systems such as Hadoop and related technologies (Spark, Trino,, etc.).
• Background in at least one programming languages (e.g. Python, Java, Scala)
• Experience working with databases that power APIs for front-end applications.
• Experience with either data workflows/modeling (Azkaban, Airflow), front-end engineering (Flask, Streamlit), or back-end engineering (Spark, DBT).
• Experience in developing data pipelines using DBT, Spark and Trino..
• Experience with data modeling, ETL (Extraction, Transformation & Load) concepts, data validation and patterns for efficient data governance.
• Deep understanding of technical and functional designs for relational and MPP Databases
• Experience working in the product analytics domains.
• Experience in data visualization and dashboard design including tools such as Tableau, R/Python visualization packages, D3, and other Javascript libraries, etc.
• Knowledge of Unix and Unix-like systems, git and version control systems..

Suggested Skills:

• Python
• Distributed Systems
• Relational Databases
• ETL

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $96,000 - $156,000. 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. 

Additional Information

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: EEO Statement_2020 - Signed.pdf.

Please reference the following information for more information: https://legal.linkedin.com/content/dam/legal/LinkedIn_EEO_Statement_2020.pdf.

Please reference the following information for more information:  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.

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 for Job Candidates ​

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.