Applied Scientist, Customer Experience and Business Trends, Customer Experience and Business Trends
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Lead a 15-20 person data science team focused on LinkedIn's growth and AI systems, mentoring junior scientists and guiding product strategy through data-driven insights. The role requires 7+ years as a data scientist, applied scientist, or data engineer with strong SQL, Python, and statistical modeling expertise, plus experience with A/B testing and experimentation. You'll work from Sunnyvale, Bellevue, New York, or remote, developing machine learning models, designing business metrics, and collaborating across product, engineering, and business teams. Salary: $174,000–$286,000.
Written from this posting by Neural Jobs AI. The full description is below.
Location:
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. This role may be remote or hybrid. At LinkedIn, hybrid roles are performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Remote roles are performed from the designated home work location upon time of hire, and any changes to this home work location requires a review of remote status and approval.
This role will be based in Sunnyvale CA, Bellevue WA, New York NY, or Remote.
Team Overview:
The Flagship Growth Data Science team focuses on accelerating LinkedIn Growth with strategic and actionable insights and measurement in close collaboration with the rest of the Growth R&D team. System Insights DS team focuses on deepening understanding of and identifying opportunities in the intricate AI systems across Flagship. We work across different Growth and Flagship Experience areas including SEO/AEO, login/signup, new members, notifications, email, networking, Feed, Search, etc. and collaborate with cross-functional partners in Product, Engineering, AI, Marketing, Business Development, Design and UER teams.
Responsibilities:
Serve as Technical Lead for Flagship Growth and AI System Insights Data Science team of 15-20 of Data Scientists. Beyond product ops & strategy and experimentations, this individual will also be leading initiatives across AI model diagnostics & enhancements, LLM-as-a-judge evaluation, and productivity improvements through AI-powered tooling.
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.
Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews.
Drive org-wide 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.
Develop and analyze experiments to test new product ideas or go to market strategies. Convert the results into actionable recommendations. Independently craft compelling stories; make logical recommendations; drive informed actions.
Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights.
Basic Qualifications:
7+ years of relevant work experience as a Data Scientist, Applied Scientist, or Data Engineer.
Bachelor or higher degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
Experience influencing strategy through data-centric presentations .
Experience in SQL, Python, and/or additional programming languages such as R and Scala.
Experience in applied statistics and statistical modeling in at least one statistical software package.
Experience running platform experiments and techniques like A/B testing
Preferred Qualifications:
At least (3) years of technical, thought, and/or team leadership experience in Data Science, Applied Science, Business Analytics, or Data Engineering.
Master’s or PhD degree in Statistics, Data Science, Engineering, Economics, Mathematics, or a related discipline.
Experience with manipulating massive-scale structured and unstructured data.
Experience mentoring and providing technical or thought leadership for other data scientists
Excellent communication skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives and compile compelling narratives.
Suggested Skills:
Technical Leadership
Experimentation & Causal Inference
Data Science
Coding with AI
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.
Compensation:
The pay range for this role is $174,000 - $286,000. 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:
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.
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