LinkedIn was built to help professionals achieve more in their careers, and everyday 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 are much more than a digital resume – we transform lives through innovative products and technology.

Creating economic opportunity for every member of the global workforce is a responsibility we all share. To truly transform the global economy, we must evolve the way we hire and enable our talent to serve people of all backgrounds and experiences. LinkedIn is committed to diversity in its workforce and is proud to be an equal opportunity employer. 

At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.

Responsibilities:

You will partner with cross-functional teams to initiate, lead, and drive to completion large-scale/complex strategic projects for teams, departments, and the company.

You will lead and manage a team of high-performing data science and data engineering professionals, and cross-functional teams to design, develop and manage core company data foundations, executive metrics and methodologies, create insightful automated dashboards and data visualization to track them and extract useful business insights

You will analyze large-scale structured and unstructured data; develop deep-dive analyses and machine learning solutions to drive member value and customer success.

You will engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights

You will act as a thought partner to senior leaders and executives to develop long-term roadmaps and strategy, prioritize/scope projects, provide recommendations and evangelize data-driven business decisions in support of strategic goals

You will provide technical guidance and mentorship to junior data scientists on analysis design and lead code/design reviews.

You will be an org-wide innovator and build/leverage the most advanced practices of research, machine learning, experimentation + causal inference, data engineering and statistical modeling to deliver significant business impact

Basic Qualifications:

BS/BA in Computer Science or related technical discipline

8+ years of industry experience

2+ years experience in managing Data Science/ Data Engineering teams

Preferred Qualifications:

10+ years of relevant work experience

Strong leadership with track records in building high performing Data Science and Data Engineering teams, driving projects, applying strategic thinking, building thought leadership, and influencing senior leaders and executives

Demonstrated ability to work with peers in engineering and product management across teams to set technical and product direction

Excellent communications skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives

Experience with manipulating massive-scale structured and unstructured data

Experience with Hadoop or other MapReduce paradigms, and associated languages such as Pig, Hive, etc.

Proficiency in SQL and at least one programming language (e.g., R, Python, Scala).

Experience influencing strategy through data-centric presentations.

Suggested Skills:

Large Scale systems

Relational Databases

ETL

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

This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal