Understanding core statistics and mathematics to analyze data, build models, and draw valid conclusions.

Proficiency in programming languages and tools essential for data manipulation, analysis, and modeling.

Ability to develop, train, and optimize machine learning models for predictive analytics and AI applications.

Transforming raw, messy data into usable formats through preprocessing, handling missing values, and feature engineering.

Presenting data insights clearly and effectively to both technical and non-technical audiences.

Working with large datasets and cloud-based tools for scalable data processing and storage.

Understanding pipelines, databases, and workflows to efficiently manage and prepare data for analysis.

Aligning data science solutions with industry-specific problems and organizational objectives.

Working effectively with cross-functional teams and communicating complex findings in a simple, actionable way.

Keeping up with emerging trends, tools, and frameworks in the fast-evolving data science ecosystem.