Cypress HCM Data Science Analyst in Bodega Bay, CA | 913239232

Data Science Analyst

Description:

Data Science Analyst, Remote, 6 month contract
We leverage 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 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 a Data Science Analyst to have an impact and transform your career.
We are looking for a Data Science Analyst to join our team. In this role, you 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.

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 LinkedIn’s vision and mission.
Analyzing large datasets to uncover trends, patterns, and insights.
Developing predictive models to forecast business outcomes and support decision-making processes.

Basic Qualifications:

Bachelor's Degree in a quantitative discipline: Computer Science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, etc.
2+ years experience in applying analytical and statistical methods to real-world business problems. Demonstrated ability to deliver actionable insights and recommendations from complex datasets to drive business decisions and outcomes.
4+ years of relevant industry or relevant academia experience working with large amounts of data
Experience with SQL/Relational databases
4+ years experience in at least one programming languages (e.g., R, Python, Java, Scala, PHP, JavaScript)

Preferred Qualifications:

BS and 2+ years of relevant work experience, MS and 2+ years of relevant work experience, or Ph.D. in quantitative discipline
MS or PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.).
Background in at least one programming languages (e.g. Python, Java, Scala, PHP, JavaScript)
Experience working with databases that power APIs for front-end applications.
Experience with either data workflows/modeling, front-end engineering, or back-end engineering.
Experience in developing data pipelines using Spark and Hive.
Experience with data modeling, ETL (Extraction, Transformation & Load) concepts, and patterns for efficient data governance.
Deep understanding of technical and functional designs for relational and MPP Databases
Experience working in the product analytics domains.
Experience in data visualization and dashboard design including tools such as Tableau, R visualization packages, D3, and other Javascript libraries, etc.
Knowledge of Unix and Unix-like systems, git and review board.

Suggested Skills:

Compensation:

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