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.