Data Insight Analyst

As a Data Analyst on a 2-month contractual basis, your main responsibilities will include: - Delving deep into existing dashboards to grasp the underlying data, key metrics, and typical user interactions. - Inferring and documenting common user journeys and potential questions (use cases) users might have regarding the data presented in the dashboards. - Translating identified use cases into precise Natural Language (NL) prompts. - Developing accurate and efficient SQL queries to retrieve data that answers the NL prompts, by exploring table schemas and business rules as required. - Creating, labeling, and validating a large volume of high-quality NL-SQL pairs. - Collaborating with business stakeholders and dashboard owners to confirm use cases, clarify business logic, and refine NL prompts. - Proactively identifying and exploring new potential use cases and insights from the dashboards. - Utilizing AI-powered tools and techniques to enhance efficiency and quality in the NL-SQL pair generation process. - Documenting findings, schemas, and business rules encountered. Qualifications required for this role: - Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Informatics, Engineering) or equivalent practical experience. - 3+ years of experience in data analysis, business intelligence, or a similar role. - Strong proficiency in SQL, including writing complex queries, joins, and aggregations. - Proven ability to analyze and interpret data presented in dashboards and reports. - Excellent communication and interpersonal skills, with the ability to facilitate discussions with technical and non-technical stakeholders. - Analytical and inquisitive mindset with a passion for understanding data and user needs. - Experience with or a strong interest in AI and machine learning concepts. - Ability to work independently and manage multiple tasks in a fast-paced environment. Preferred qualifications include: - Familiarity with Data Center operations, metrics, or data. - Experience with data labeling or dataset creation for machine learning models. - Familiarity with data platforms and tools. As a Data Analyst on a 2-month contractual basis, your main responsibilities will include: - Delving deep into existing dashboards to grasp the underlying data, key metrics, and typical user interactions. - Inferring and documenting common user journeys and potential questions (use cases) users might have regarding the data presented in the dashboards. - Translating identified use cases into precise Natural Language (NL) prompts. - Developing accurate and efficient SQL queries to retrieve data that answers the NL prompts, by exploring table schemas and business rules as required. - Creating, labeling, and validating a large volume of high-quality NL-SQL pairs. - Collaborating with business stakeholders and dashboard owners to confirm use cases, clarify business logic, and refine NL prompts. - Proactively identifying and exploring new potential use cases and insights from the dashboards. - Utilizing AI-powered tools and techniques to enhance efficiency and quality in the NL-SQL pair generation process. - Documenting findings, schemas, and business rules encountered. Qualifications required for this role: - Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Informatics, Engineering) or equivalent practical experience. - 3+ years of experience in data analysis, business intelligence, or a similar role. - Strong proficiency in SQL, including writing complex queries, joins, and aggregations. - Proven ability to analyze and interpret data presented in dashboards and reports. - Excellent communication and interpersonal skills, with the ability to facilitate discussions with technical and non-technical stakeholders. - Analytical and inquisitive mindset with a passion for understanding data and user needs. - Experience with or a strong interest in AI and machine learning concepts. - Ability to work independently and manage multiple tasks in a fast-paced environment. Preferred qualifications include: - Familiarity with Data Center operations, metrics, or data. - Experience with data labeling or dataset creation for machine learning models. - Familiarity with data platforms and tools.