Staff Software Engineer, Data Science

Founded in 2003, LinkedIn connects the world's professionals to make them more productive and successful. With more than 1 billion members worldwide, including executives from every Fortune 500 company, LinkedIn is the world's largest professional network. The company has a diversified business model with revenue coming from Talent Solutions, Marketing Solutions, Sales Solutions and Premium Subscriptions products. Headquartered in Silicon Valley, LinkedIn has offices across the globe..

linkedin.com

HQUS

Team Size26000

Open Jobs1132

Total Funding-

Latest FundraiseUnknown

TL;DR

Founded: 2003 (launched May 2003; company formed Dec 2002)

Headquarters: Sunnyvale, California

Members: Over 1 billion

Employee count: Approximately 26,000 (source snapshot)

Revenue streams: Talent Solutions, Marketing Solutions, Sales Solutions, Premium Subscriptions

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Company Overview

Problem Domain

Professional networking, recruiting, sales enablement, and professional learning.

Founded

2003

Industry

Software Development

Funding Track Record

Venture / Growth rounds- Jan 28, 2007

$12.8M

Reported previously rumored $12.8M round

Series D- Jun 17, 2008

$53M

Investors included Sequoia, Greylock, Bessemer and Bain Capital Ventures; reported ~ $1B valuation

Follow-on / strategic investment- Oct 22, 2008

$22.7M

Follow-on infusion from strategic investors including SAP, Goldman Sachs, and McGraw‑Hill

Investor Signal

“Sequoia Capital, Greylock Partners, Bessemer Venture Partners, Bain Capital Ventures and strategic investors (SAP, Goldman Sachs, McGraw‑Hill) participated in private rounds prior to IPO.”

Founders

What we do

Join the Team

HybridBengaluru, Karnataka, IN

Hybrid • Bengaluru, Karnataka, IN

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 LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology.

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.

About the team:

LinkedIn’s Trust \ team's goal is to leverage big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to create a Trusted and Safe Platform, drive member engagement, business growth and monetization . With over 800 million 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.

The Trust Data Science team delivers data & metrics insights, develops data platforms / tools and enables decisions at scale through inference and algorithm as part of the cross-functional Trust team to realize its mission to create safe, trusted, professional experiences where individuals and organizations can be productive and successful. In this role we are looking for a technical leader in the Trust Data Engineering and Platform team. This person will work closely with various cross-functional teams such as product, engineering, and operations to develop infrastructure and deliver tools or data structures that enable data-driven decision-making. Successful candidates will exhibit technical acumen and business savviness with a passion for making an impact by enabling both producers and consumers of data insight to work smarter.

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.

Qualifications

Bachelor's Degree in a quantitative discipline: Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, etc
8+ years of relevant industry or relevant academia experience working with large amounts of data
Experience with SQL/Relational databases.
Experience with Apache Spark and Presto.
Background in at least one programming languages (e.g., R, Python, Java, Scala)

Preferred Qualifications

BS and 10+ years of relevant work experience, MS and 7+ years of relevant work experience, or Ph.D. and 4+ 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.

Additional Information Suggested Skills :

Data Modelling
Distributed Systems
Relational Databases
Technical Leadership
Data Manipulation

India Disability Policy LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf

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.

LinkedIn