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About the job
Role: Data Science & Analytics(DSA) Experience:5 years location: US About This Role You will play a key role in executing our global analytics strategy and elevating junior data analysts' technical skills. Your responsibilities include developing and improving business-focused reporting and visualization suites, writing clear code, and creating accurate technical documents. You'll collaborate with engineers, scientists, and product managers to turn business requirements into scalable solutions, and provide training to business analysts. You will address complex business challenges, build data pipelines, automate data processes, and ensure ETL/ELT processes are robust and scalable. Effective communication and problem-solving are essential, along with a commitment to continuous learning Responsibilities
Develop and maintain data models (conceptual, logical, and physical) to support analytics and reporting needs.
Create and manage data dictionaries, ER diagrams, and schema designs that align with business requirements.
Collaborate with data architects and stakeholders to define data modeling standards and best practices.
Utilize code (SQL, python, etc.) and apply engineering, reporting, and visualization expertise to solve business problems. Develop scalable tools to drive automation and optimize business operations.
Develop and lead a team of junior data analyst, providing mentorship, training, and coaching to increase technical acumen across the team.
Develop scalable systems to expand reporting capabilities, facilitate ad hoc analysis, and improve data-driven decision making at all levels of the business.
Work with large, complex data sets. Solve difficult data transformation problems with efficiency, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
Contribute to the establishment of standards for writing clean, organized code and documentation to streamline data and analytics workflow.
Drive and promote a culture of testing, observability, and scalability with a data-driven mindset
Manage and continuously improve business users experience with data and reporting, including KPI development, data visualization, and communication of applicable insights to audiences at varying levels of technical sophistication. Increase overall data literacy across ELC through education and advocacy.
Develop partnerships with engineering, data science, and product teams to deliver on major cross-functional reporting, measurement, and testing efforts.
Actively participate in ELCs diversity and inclusion agenda.
Requirements
BS/BA in a quantitative field; a plus if MS degree in a quantitative discipline (e.g., Statistics, Operations Research, Economics, Computer Science, Mathematics, Engineering) or equivalent practical experience.
4+ years of experience in Data Warehouse Data Modeling techniques.
4+ years of experience (2+ with a graduate degree) in Analytics, Data Science, or Software Engineering, both as an individual contributor and managing teams; including expertise with descriptive statistical analysis and data transformation
Experience with analytics software such as Looker, PowerBI, Tableau, or similar open-source tools
4+ years of experience with database languages (SQL, etc...). 1+ year of experience with data scripting languages or statistical/mathematical software (Python, R, Matlab, etc.) is a plus
Track record of delivering data-driven products and insights as well as influencing product and engineering decisions.
Significant experience working with large-scale cloud database systems (e.g., BigQuery). Broad Knowledge of best practices in large- and small-scale data processing
Experience in analyzing, validating, and transforming large datasets.
Proficiency in deploying data-intensive solutions. Solid understanding of the software development lifecycle.
4+ years of hands-on experience in crafting compelling data visualizations to inform business decisions
Desired Skills and Experience
Data Warehousing, Microsoft Power BI, Tableau, SQL, Python (Programming Language), Google BigQuery, Data Science, Data Analysis
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