• Data Wrangling:Clean, transform, and prepare raw datasets for downstream analytics and modeling.

• Pipeline Engineering:Help build scalable data pipelines that move data between systems reliably.

• Analytics:Conduct exploratory and descriptive analyses to uncover insights that drive client decisions.

• Predictive Modeling:Develop and validate machine-learning models for client business problems.

• Cross-Team Collaboration:Work with product, engineering, and business teams to translate requirements into deliverables.

• Code Quality:Follow standards for code reviews, testing, and documentation across the data stack.

• Learning & Growth:Participate in training, knowledge-sharing sessions, and project demos to grow your skill base.