Data Science Analyst

As a Data Analyst with 5+ years of experience, you will be responsible for supporting the development of realistic AI benchmarking environments by leveraging your expertise in SQL, product analytics, and BigQuery. Your deep knowledge of product event data systems, dimensional modeling, and data quality troubleshooting in large-scale analytics ecosystems will be crucial in creating and reviewing BigQuery schemas, event taxonomies, SQL queries, metric definitions, and data artifacts. Key Responsibilities: - Design and define scalable BigQuery schemas and analytical data models. - Build and optimize complex SQL queries using CTEs, joins, and window functions. - Create and maintain dimensional data models including fact and dimension tables. - Work with product event tracking platforms such as Segment, Amplitude, or Mixpanel. - Develop realistic event taxonomies, product metrics, and analytical datasets. - Identify, troubleshoot, and resolve data quality issues across analytics systems. - Analyze discrepancies between dashboards, reports, and source systems. - Collaborate with cross-functional teams to ensure consistency in metric definitions and reporting standards. - Review analytical artifacts and validate their technical correctness. - Contribute to AI benchmark development by simulating realistic analytical environments and scenarios. Mandatory Skills: - Strong SQL expertise including complex queries, CTEs (Common Table Expressions), and window functions. - Strong understanding of dimensional modeling: Fact tables, Dimension tables. - Experience with product event analytics platforms: Segment, Amplitude, Mixpanel. - Hands-on experience with BigQuery. - Expertise in handling data quality challenges and implementing resolution strategies. - Strong analytical and problem-solving abilities. Required Qualifications: - 5+ years of experience in Data Analytics or Data Science. - Experience working with large-scale analytical datasets and product data ecosystems. - Strong understanding of product metrics, event tracking, and analytical reporting. - Experience designing realistic and scalable analytical data structures. - Ability to communicate technical concepts and data discrepancies clearly to stakeholders. As a Data Analyst with 5+ years of experience, you will be responsible for supporting the development of realistic AI benchmarking environments by leveraging your expertise in SQL, product analytics, and BigQuery. Your deep knowledge of product event data systems, dimensional modeling, and data quality troubleshooting in large-scale analytics ecosystems will be crucial in creating and reviewing BigQuery schemas, event taxonomies, SQL queries, metric definitions, and data artifacts. Key Responsibilities: - Design and define scalable BigQuery schemas and analytical data models. - Build and optimize complex SQL queries using CTEs, joins, and window functions. - Create and maintain dimensional data models including fact and dimension tables. - Work with product event tracking platforms such as Segment, Amplitude, or Mixpanel. - Develop realistic event taxonomies, product metrics, and analytical datasets. - Identify, troubleshoot, and resolve data quality issues across analytics systems. - Analyze discrepancies between dashboards, reports, and source systems. - Collaborate with cross-functional teams to ensure consistency in metric definitions and reporting standards. - Review analytical artifacts and validate their technical correctness. - Contribute to AI benchmark development by simulating realistic analytical environments and scenarios. Mandatory Skills: - Strong SQL expertise including complex queries, CTEs (Common Table Expressions), and window functions. - Strong understanding of dimensional modeling: Fact tables, Dimension tables. - Experience with product event analytics platforms: Segment, Amplitude, Mixpanel. - Hands-on experience with BigQuery. - Expertise in handling data quality challenges and implementing resolution strategies. - Strong analytical and problem-solving abilities. Required Qualifications: - 5+ years of experience in Data Analytics or Data Science. - Experience working with large-scale analytical datasets and product data ecosystems. - Strong understanding of product metrics, event tracking, and analytical reporting. - Experience designing realistic and scalable analytical data structures. - Ability to communicate technical concepts and data discrepancies clearly to stakeholders.