Data and AI Analyst

Job Summary

We are looking for a Data & AI Analyst with 1–3 years of experience to support data analysis, reporting, business intelligence, and AI-driven solutions. The ideal candidate should have strong analytical skills and experience working with SQL, Python, data visualization, machine learning concepts, and AI tools.

The Data & AI Analyst will work with business and technical teams to analyze data, identify trends, build dashboards and reports, and support the development and implementation of AI and automation solutions

Key Responsibilities

• Analyze business processes and data to identify opportunities for AI, automation, and improved decision-making.
• Collect, clean, and analyze structured and unstructured data to support business and AI initiatives.
• Build and maintain dashboards, reports, and KPIs using tools such as Power BI or Tableau.
• Write SQL queries to extract, transform, and analyze data from multiple sources.
• Use Python for data analysis, data preparation, and basic automation.
• Support AI/ML initiatives by preparing datasets, evaluating results, and tracking model performance.
• Assist with Generative AI and LLM-based use cases, including prompt testing and output validation.
• Identify data-quality issues and work with technical teams to resolve them.
• Translate business requirements into analytical questions and actionable insights.
• Present findings and recommendations to both technical and non-technical stakeholders.
• Maintain clear documentation of data sources, analysis, AI use cases, and business outcomes.

Preferred Qualifications & Requirements

• Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, Business Analytics, or a related field.
• 1–3 years of experience in data analysis, business analytics, or applied AI/ML.
• Proficiency in SQL and at least one analytics language such as Python or R.
• Experience with Power BI, Tableau, or similar BI tools.
• Familiarity with core AI/ML concepts, including classification, regression, NLP, and basic model evaluation.
• Understanding of Generative AI, LLMs, and prompt engineering.
• Strong analytical and problem-solving skills with attention to data quality.
• Ability to translate business problems into analytical solutions and communicate findings clearly.
• Ability to work effectively with business, IT, data engineering, and other cross-functional teams.