Senior Staff Applied Scientist, Infrastructure DS

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.

LinkedIns 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 a career at LinkedIn offers countless ways for an ambitious data scientist to have an impact.

We are seeking a talented and driven individual to accelerate our efforts and contribute to LinkedIns data-centric this role you will tackle a wide range of technical challenges spanning products engineering research data engineering finance and infrastructure. Leveraging data and analysis you will address critical challenges within our infrastructure organization shaping product strategy and guiding investment decisions with data-driven insights.

LinkedIns infrastructure is the backbone of our operations encompassing data centers servers network infrastructure power systems and foundational software platforms that power our products and services.

As an Applied Scientist in LinkedIn Infrastructure youll develop and apply rigorous quantitative methods to optimize the systems that power our global platform. Your work will focus on forecasting inference and optimization across data centers compute network and power systems while also designing signal-driven monitoring and alerting models to detect risk anomalies and degradation in real time and building measurement frameworks that quantify and attribute infrastructure cost performance and reliability to different products and lines of business where accuracy resilience and scale are critical.

Responsibilities:

• Provide direction and oversight for in-depth and rigorous causal inference 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 working 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 org and company

Qualifications :

Basic Qualifications:

• B.S. Degree in a quantitative discipline: Statistics Operations Research Computer Science Informatics Engineering Applied Mathematics Economics etc.
• 5 years experience with SQL or relational database query performance and at least one programming language (e.g. R Python Scala)
• 2 years experience in an architect or technical leadership position

Preferred Qualifications:

• 10 years of overall experience with at least 5 of those years leading teams technically
• Experience influencing strategy through data-centric presentations
• 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
• Ability to work with multiple stakeholders understand the product priorities think with the big picture and solve core problems in the most efficient way
• Experience with manipulating massive-scale structured and unstructured data
• Proven record writing and optimizing code with high levels of craftsmanship and coaching others to improve technical outputs
• Experience mentoring other data scientists in an official or unofficial capacity
• Excellent communication skills with the ability to synthesize simplify and explain complex problems to different types of audience including executives and compile compelling narratives
• Demonstrated thought leadership; experience publishing publicly visible research papers and/or speaking at conferences.
• MS or PhD in a quantitative discipline: Statistics Economics Applied Mathematics Operations Research Computer Science Informatics Engineering etc.

Suggested Skills:

• Statistical Modeling
• Forecasting
• Programming
• Data Analysis
• Infrastructure Planning

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 $198000 - $326000. 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 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.

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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 LinkedIns legal duty to furnish information.

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Pursuant to the San Francisco Fair Chance Ordinance LinkedIn will consider for employment qualified applicants with arrest and conviction records.

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No

Employment Type :

Full-time