Data Scientist, Analytics at Meta

Menlo Park, California, United States -

Full Time

Start Date

Immediate

Expiry Date

26 Jun, 26

Salary

235400.0

Posted On

28 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Warehousing, Data Modeling, ETL, SQL, Data Extraction, Data Transformation, Data Loading, Data Quality, Data Security, A/B Testing, Opportunity Sizing, Visualization, Query Optimization, SLA Management, Dimensional Modeling, Data Analysis

Industry

Software Development

Description

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page. Responsibilities Design, model, or implement data warehousing activities in order to contribute to the design and development of Meta products. Manage and execute data warehouse plans for a product or a group of products to solve well-scoped problems. Identify the data needed for a business problem and implement logging required to ensure availability of data, while working with data infrastructure to triage issues and resolve. Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights visually in a meaningful way. Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership. Design, build and launch new data models and visualizations in production, leveraging common development toolkits. Independently design, build and launch new data extraction, transformation and loading processes in production, mentoring others around creating efficient queries. Support existing processes running in production and implement optimized solutions with limited guidance. Define and manage SLA for data sets in allocated areas of ownership. Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors. Demonstrate good judgment in selecting methods and techniques for obtaining solutions. May telecommute from anywhere in the US. Conduct opportunity sizing analysis to determine the impact of specific initiatives and the return on investment. Conduct A/B testing to understand the incremental changes to product performance and user behavior as a result of changes in product features or infrastructure. Collaborate with stakeholder to communicate analytical insights and determine product strategy. Minimum Qualifications Requires a Bachelor's degree (or foreign degree equivalent) in Business Administration, Computer Science, Engineering, Information Systems, Mathematics, Statistics, Data Analytics, Applied Sciences, or a related field and five years of progressive, post-baccalaureate work experience in the job offered or in a computer-related occupation Requires five years of experience in the following: Custom ETL design, implementation, and maintenance Schema design and dimensional data modeling Writing SQL statements Analyzing data to identify deliverables, gaps and inconsistencies Managing and communicating data warehouse plans to internal clients Experience in a quantitative field, such as consulting, market research, media research Experience in working with large datasets and using SQL or similar tools for data extraction and manipulation Experience communicating complex concepts to non-technical audiences and Direct experience scoping and executing research projects with clients and or cross-functional stakeholders $232,268/year to $235,400/year + bonus + equity + benefits

Responsibilities

Responsibilities include designing, modeling, and implementing data warehousing activities to contribute to product development, managing data warehouse plans for products, and identifying necessary data while collaborating with engineers and product managers. The role also involves building data expertise, ensuring compliance, and launching new data models and ETL processes in production.