Data scientists are responsible for building and deploying machine learning models to solve real-world problems. They use a variety of programming languages and tools to collect, clean, and analyze data, and then they develop and implement machine learning models to make predictions or recommendations.
Machine learning engineers are responsible for designing, developing, and deploying machine learning systems at scale. They work closely with data scientists to identify and solve business problems using machine learning.
Data engineers are responsible for building and maintaining the infrastructure that supports data analysis. They develop and manage data pipelines, data warehouses, and data lakes. They also work with data scientists and machine learning engineers to ensure that they have the data they need to do their work.
Business intelligence analysts use data to help businesses make better decisions. They collect, clean, and analyze data to create reports and dashboards that can be used to track performance, identify trends, and highlight opportunities.
Marketing analysts use data to understand customer behavior and develop effective marketing campaigns. They collect and analyze data on customer demographics, purchase history, and website interactions to identify trends and patterns. They then use these insights to develop and implement marketing campaigns that are more likely to be successful.
Quantitative analysts use mathematical and statistical methods to analyze data to solve financial and business problems. They work in a variety of industries, including investment banking, risk management, and insurance.
Data architects design and implement data management systems for businesses. They work with business stakeholders to understand their data needs and then design systems that can meet those needs. They also oversee the implementation and maintenance of these systems.