Staff Software Engineer, Data Science

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 monetisation efforts. 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.

We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture. This person will work closely with various cross-functional teams such as product marketing sales 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.
- Perform all of the necessary data transformations to serve products that empower data-driven decision making.
- Establish efficient design and programming patterns for engineers as well as for non-technical partners.
- Design implement integrate and document performant systems or components for data flows or applications that power analysis at a massive scale.
- Ensure best practices and standards in our data ecosystem are shared across teams.
- Understand the analytical objectives to make logical recommendations and drive informed actions.
- Engage with internal data platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms.
- Contribute to engineering innovations that fuel LinkedIns vision and mission.

Qualifications :

Basic Qualifications:
- Bachelors 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
- Background in at least one programming languages (e.g. R Python Java Scala PHP JavaScript)

Preferred Qualifications:
- BS and 10 years of relevant work experience MS and 9 years of relevant work experience or Ph.D.
- Experience in developing data pipelines using Spark and Hive.
- Experience with data modeling ETL (Extraction Transformation & Load) concepts and patterns
for efficient data governance.
- Experience in either the front-end or back-end development of data-powered applications.
- Deep understanding of technical and functional designs for relational and MPP Databases
- Reporting and Data Mining systems.
- Experience working in the product sales or marketing analytics domains.
- Experience in data visualisation and dashboard design including tools such as Tableau R
visualisation packages D3 and other JavaScript libraries etc.
- Published work in academic conferences or industry circles

Suggested Skills :
Data Pipeline
Data Engineering
Data Manipulation

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.

Additional Information :

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 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: Work :

No

Employment Type :

Full-time