Senior Data Scientist – Strategy & Insights

LinkedIn is the world’s largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters.

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, 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, policy and operations to develop and deliver metrics, analyses, solutions, and insights, with actionable recommendations to business partners. Successful candidates will exhibit technical acumen, product sense and business savvy, with a passion for making an impact through creative storytelling and timely actions.

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 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:

• Partner with cross-functional teams to contribute towards completion of large-scale/complex strategic projects for teams, departments and the company.

• Drive impact by shaping product and business strategy through data-centric presentations.

• Work with a team of high-performing data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy.

• Analyze large-scale structured and unstructured data; develop deep-dive analyses and machine learning models to drive member value and customer success.

• Design and develop core business metrics, create insightful automated dashboards and data visualization to track them and extract useful business and product insights.

• Design and analyze experiments to test new product ideas or go to market strategies. Convert the results into actionable recommendations.

• Engage with technology partners to build, prototype and validate scalable tools/applications end to end (backend, frontend, data) for converting data to insights.

• Mentor junior members of the team.

Basic Qualifications:

• Bachelor’s Degree in a quantitative discipline: Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, etc.

• 3+ years of relevant industry or relevant academia experience working with large amounts of data

• Experience influencing strategy through data-centric presentations.

• Experience in SQL.

• Background in at least one programming language (e.g., R, Python, Scala).

• Experience in applied statistics and statistical modeling in at least one statistical software package.

• Experience telling stories with data and visualization tools.

• Experience running platform experiments and techniques like A/B testing.

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 working with large amounts of data

• MS or PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.

• Experience with manipulating massive-scale structured and unstructured data.

• Working knowledge of Unix command-line/shell, git and review board.

• Experience leveraging government data or publicly available third-party APIs.

• Excellent communication skills, with the ability to synthesize, simplify and explain complex problems to different types of audience.

Suggested Skills:

• SQL

• Python

• Statistical Analysis

• Data Storytelling

• Data Interpretation

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