Sr Software Engineer, Data Science
LinkedIn
Full-time
On-site
Bengaluru Karnataka India
Company 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.
Creating economic opportunities 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.
Job Description
This role will be based in Bangalore, India.
At LinkedIn, our approach to flexible work is centred 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.
LinkedIn’s Data Science team leverages big data to empower business decisions. The Trust Data Science team at LinkedIn works in close partnership with the trust engineering, content moderator and product teams to identify opportunities to develop and enhance LinkedIn member experiences. A few examples include: enabling our trust & security team (content reviewers) to be effective through data driven insights and minimize damage to our members, optimize member account access experience while defending attacks, provide insights to improve feed content quality on site, analyze trust/security features’ performance through product A/B testing, etc.
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 product managers, content moderation team, engineers, designers, product marketing, and the trust infrastructure team to develop and deliver tools or data structures that provide actionable recommendations to business partners. Successful candidates will exhibit technical acumen and business savvy, 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 analytics, data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy
Build data expertise, act like an owner for the company and manage complex data systems for a product or a group of products
Performing all of the necessary data transformations to serve products that empower data-driven decision making
Establishing efficient design and programming patterns for engineers as well as for non-technical partners
Designing, integrating and documenting technical components for data flows or applications that perform analysis at a massive scale
Ensuring 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 platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms
Initiate and drive projects to completion with minimal guidance
Contribute to engineering innovations that fuel LinkedIn’s vision and mission
Qualifications
Bachelor in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
5+ years relevant industry or relevant academia experience working with large amounts of data
3 + years' experience with SQL/Relational databases
3 + years' experience with manipulating massive-scale structured and unstructured data.
Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.).
Background in at least one programming language (e.g., R, Python, Java, Scala, PHP, JavaScript)
Experience with data modelling, ETL (Extraction, Transformation & Load) concepts, and patterns for efficient data governance.
Working knowledge of Unix and Unix-like systems, git and review board.
Additional Information
Preferred Qualifications:
Masters or Ph.D. degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
Bachelors with 5+ years or Masters with 3+ years of industry experience
Experience in developing data pipelines using Spark and Hive
Experience with either data workflows/modeling, front-end engineering, or back-end engineering
Experience in either the front-end or back-end development of data-powered applications.
Suggested Skills:
Deep understanding of technical and functional designs for relational and MPP Databases, Reporting and Data Mining systems
Strong communication skills, with the ability to synthesize, simplify and explain complex problems to different audiences.
Experience working with databases that power APIs for front-end applications.
Experience in data visualization and dashboard design including tools such as Tableau, R visualization packages, D3, and other Javascript libraries, etc.
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 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.
Creating economic opportunities 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.
Job Description
This role will be based in Bangalore, India.
At LinkedIn, our approach to flexible work is centred 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.
LinkedIn’s Data Science team leverages big data to empower business decisions. The Trust Data Science team at LinkedIn works in close partnership with the trust engineering, content moderator and product teams to identify opportunities to develop and enhance LinkedIn member experiences. A few examples include: enabling our trust & security team (content reviewers) to be effective through data driven insights and minimize damage to our members, optimize member account access experience while defending attacks, provide insights to improve feed content quality on site, analyze trust/security features’ performance through product A/B testing, etc.
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 product managers, content moderation team, engineers, designers, product marketing, and the trust infrastructure team to develop and deliver tools or data structures that provide actionable recommendations to business partners. Successful candidates will exhibit technical acumen and business savvy, 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 analytics, data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy
Build data expertise, act like an owner for the company and manage complex data systems for a product or a group of products
Performing all of the necessary data transformations to serve products that empower data-driven decision making
Establishing efficient design and programming patterns for engineers as well as for non-technical partners
Designing, integrating and documenting technical components for data flows or applications that perform analysis at a massive scale
Ensuring 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 platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms
Initiate and drive projects to completion with minimal guidance
Contribute to engineering innovations that fuel LinkedIn’s vision and mission
Qualifications
Bachelor in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
5+ years relevant industry or relevant academia experience working with large amounts of data
3 + years' experience with SQL/Relational databases
3 + years' experience with manipulating massive-scale structured and unstructured data.
Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.).
Background in at least one programming language (e.g., R, Python, Java, Scala, PHP, JavaScript)
Experience with data modelling, ETL (Extraction, Transformation & Load) concepts, and patterns for efficient data governance.
Working knowledge of Unix and Unix-like systems, git and review board.
Additional Information
Preferred Qualifications:
Masters or Ph.D. degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
Bachelors with 5+ years or Masters with 3+ years of industry experience
Experience in developing data pipelines using Spark and Hive
Experience with either data workflows/modeling, front-end engineering, or back-end engineering
Experience in either the front-end or back-end development of data-powered applications.
Suggested Skills:
Deep understanding of technical and functional designs for relational and MPP Databases, Reporting and Data Mining systems
Strong communication skills, with the ability to synthesize, simplify and explain complex problems to different audiences.
Experience working with databases that power APIs for front-end applications.
Experience in data visualization and dashboard design including tools such as Tableau, R visualization packages, D3, and other Javascript libraries, etc.
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.