Azure Data Analyst

Job Description As a Data Analyst with 3+ years of experience, your role will involve collecting, analyzing, and interpreting large datasets to support business decision-making. You will play a pivotal role in enabling data-driven decision-making by extracting insights from complex datasets. Your responsibilities will include: - Analyzing structured and unstructured data to identify trends, patterns, and actionable insights for AI/ML and Gen AI initiatives. - Supporting the development of Gen AI use cases by preparing datasets for training, fine-tuning, and evaluation. - Collaborating with data scientists to validate model outputs and ensure alignment with business KPIs. - Building dashboards and visualizations to communicate insights and model performance to stakeholders. - Performing data profiling, cleansing, and transformation to ensure high-quality inputs for AI pipelines. - Contributing to the development of synthetic datasets and prompt libraries for Gen AI experimentation. - Documenting data lineage, metadata, and quality metrics to support governance and compliance. - Assisting in the evaluation of vector embeddings, RAG pipelines, and LLM outputs for accuracy and relevance. In terms of technical skills, you should be proficient in: - Languages: SQL (advanced), Python (preferred), R (optional) - Data Platforms: Azure Data Lake, Snowflake, Databricks, Synapse Analytics - Visualization: Power BI, Tableau, Streamlit - Data Engineering: Azure Data Factory, Pandas - ML/AI Familiarity: Understanding of LLMs, RAG, embeddings, prompt tuning - Version Control & DevOps: Git, Azure DevOps - Governance: Familiarity with data privacy, security, and compliance frameworks (e.g., GDPR) Qualifications required for this role include: - Bachelors or Master's degree in Computer Science, Data Science, Statistics, or related field. - 35 years of experience in data analysis, with exposure to AI/ML or Gen AI projects. - Strong analytical and problem-solving skills with a keen eye for detail. - Excellent communication skills to translate data insights into business value. - Experience working in agile, cross-functional teams. As a Data Analyst with 3+ years of experience, your role will involve collecting, analyzing, and interpreting large datasets to support business decision-making. You will play a pivotal role in enabling data-driven decision-making by extracting insights from complex datasets. Your responsibilities will include: - Analyzing structured and unstructured data to identify trends, patterns, and actionable insights for AI/ML and Gen AI initiatives. - Supporting the development of Gen AI use cases by preparing datasets for training, fine-tuning, and evaluation. - Collaborating with data scientists to validate model outputs and ensure alignment with business KPIs. - Building dashboards and visualizations to communicate insights and model performance to stakeholders. - Performing data profiling, cleansing, and transformation to ensure high-quality inputs for AI pipelines. - Contributing to the development of synthetic datasets and prompt libraries for Gen AI experimentation. - Documenting data lineage, metadata, and quality metrics to support governance and compliance. - Assisting in the evaluation of vector embeddings, RAG pipelines, and LLM outputs for accuracy and relevance. In terms of technical skills, you should be proficient in: - Languages: SQL (advanced), Python (preferred), R (optional) - Data Platforms: Azure Data Lake, Snowflake, Databricks, Synapse Analytics - Visualization: Power BI, Tableau, Streamlit - Data Engineering: Azure Data Factory, Pandas - ML/AI Familiarity: Understanding of LLMs, RAG, embeddings, prompt tuning - Version Control & DevOps: Git, Azure DevOps - Governance: Familiarity with data privacy, security, and compliance frameworks (e.g., GDPR) Qualifications required for this role include: - Bachelors or Master's degree in Computer Science, Data Science, Statistics, or related field. - 35 years of experience in data analysis, with exposure to AI/ML or Gen AI projects. - Strong analytical and problem-solving skills with a keen eye for detail. - Excellent communication skills to translate data insights into business value. - Experience working in agile, cross-functional teams.