Linkedin Data Analyst Jobs (NOW HIRING)

Company Description
LinkedIn is the worlds 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. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. Join us to transform the way the world works.
Job Description
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 around the world, a focus on great user experience, and a mix of B2B and B2C programs, LinkedIn offers countless ways for an ambitious data engineer to have an impact and transform your career.
We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture. This person will work closely with various cross-functional teams such as product, marketing, sales, engineering, policy and operations to develop and deliver metrics, analyses, solutions, and insights, with actionable recommendations to business partners. Successful candidates will exhibit technical acumen, product sense and business savvy, with a passion for making an impact through creative storytelling and timely actions.
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.
Responsibilities

• Partner with cross-functional teams to contribute towards completion of large-scale/complex strategic projects for teams, departments and the company.
• Drive impact by shaping product and business strategy through data-centric presentations.
• Work with a team of high-performing data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy.
• Analyze large-scale structured and unstructured data; develop deep-dive analyses and machine learning models to drive member value and customer success.
• Design and develop core business metrics, create insightful automated dashboards and data visualization to track them and extract useful business and product insights.
• Design and analyze experiments to test new product ideas or go to market strategies. Convert the results into actionable recommendations.
• Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights.
• Mentor junior members of the team.

Qualifications
Basic Qualifications

• Bachelor's Degree in a quantitative discipline: Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, etc.
• 3+ years of relevant industry or relevant academia experience working with large amounts of data
• Experience influencing strategy through data-centric presentations.
• Experience in SQL.
• Background in at least one programming language (e.g., R, Python, Scala).
• Experience in applied statistics and statistical modeling in at least one statistical software package.
• Experience telling stories with data and visualization tools.
• Experience running platform experiments and techniques like A/B testing.

Preferred Qualifications

• BS and 5+ years of relevant work experience, MS and 3+ years of relevant work experience, or Ph.D. and 1+ years of relevant work/academia experience working with large amounts of data
• MS or PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
• Experience with manipulating massive-scale structured and unstructured data.
• Working knowledge of Unix command-line/shell, git and review board.
• Experience leveraging government data or publicly available third-party APIs.
• Excellent communication skills, with the ability to synthesize, simplify and explain complex problems to different types of audience.

Suggested Skills

• SQL
• Python
• Statistical Analysis
• Data Storytelling
• Data Interpretation

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 $121,000.00 to $198,000.00. 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
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.
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• Documents in alternate formats or read aloud to you
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