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Senior Applied Scientist Job Opening In Mountain View – Now Hiring LinkedIn


Job 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.

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

We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture.

It is expected that this person understands experimentation and/or machine learning techniques to be able to implement from scratch and have the ability to extend and enhance these techniques to specific applications like business problems.

Successful candidates will exhibit technical acumen on inference and algorithms, and the business savviness to use these technical skills to drive better business decision-making.

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

+ Work with a team of high-performing analytics, data science professionals, and cross-functional teams to identify business opportunities and develop algorithms and methodologies to address them.
+ 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

+ Bachelor's Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.
+ 3+ years of industry or relevant academia experience
+ Background in at least one programming language (eg.

R, Python, Java, Ruby, Scala/Spark or Perl)
+ Experience in applied statistics and statistical modeling in at least one statistical software package, (eg.

R, Python)

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
+ MS or PhD in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.

Suggested Skills

+ Machine Learning
+ Research
+ Causal Inference

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 $139,000.00 to $229,000.00 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.

**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 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.


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Unlock Your Senior Applied Potential: Insight & Career Growth Guide


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Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Senior Applied in Mountain View, United States, highlighting market share and opportunities for professionals in Senior Applied roles.

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Are You Looking for Senior Applied Scientist Job?

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at LinkedIn adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying United States laws and regulations

What Is the Average Salary Range for Senior Applied Scientist Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Mountain View. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for Senior Applied Scientist typically include Other General and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Senior Applied Scientist Job Success

LinkedIn interview tips for Senior Applied Scientist

Here are some tips to help you prepare for and ace your Senior Applied Scientist job interview:

Before the Interview:

Research: Learn about the LinkedIn's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

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Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Senior Applied Scientist interview at LinkedIn, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the LinkedIn's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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