Turning messy data into answers, predictions, and decisions, for businesses, hospitals, sports teams, and governments.
Top pay: highest pay, longest training
Data Scientist: Uses statistics, programming, and machine learning to find patterns in data and help organizations make decisions. Typical pay $120k.
Data Engineer: Builds the pipelines and warehouses that collect, clean, and move huge amounts of data so others can use it. Typical pay $135k.
Database Architect: Designs how an organization stores and organizes its data so it's fast, safe, and useful. Typical pay $140k.
Analytics Engineer: Sits between data engineers and analysts, turning raw data into clean, trustworthy tables and metrics. Typical pay $120k.
Biostatistician: Designs studies and analyzes data for medical research and drug trials. Typical pay $115k.
Chief Data Officer: The executive in charge of all of a company's data: how it is stored, protected, and used for decisions and AI. Typical pay $250k.
Analytics Manager: Leads a team of data analysts and decides which business questions they should answer first. Typical pay $145k.
Data Product Manager: Runs data tools and datasets like products, deciding what to build so others in the company can use data easily. Typical pay $160k.
Knowledge Graph Engineer: Builds maps of facts and how they connect, such as drugs, genes and diseases, so search engines and AI systems can look things up and reason. Typical pay $140k.
Mid pay: solid pay, degree or apprenticeship
Data Analyst: Answers business questions by pulling, analyzing, and visualizing data. Typical pay $80k.
Business Intelligence Analyst: Builds dashboards and reports that help leaders track how a business is doing. Typical pay $100k.
Database Administrator: Keeps an organization's databases running, backed up, secure, and fast. Typical pay $105k.
Operations Research Analyst: Uses math and computer models to help organizations solve complex problems like routing trucks or scheduling airline crews. Typical pay $93k.
Statistician: Designs surveys and experiments and uses math to figure out what data really says. Typical pay $105k.
Sports Analytics Analyst: Uses data to help sports teams pick players, plan strategy, and keep athletes healthy. Typical pay $80k.
People Analytics Analyst: Analyzes data about employees to improve hiring, pay fairness, and why people quit. Typical pay $95k.
Fraud Data Analyst: Spots suspicious transactions and patterns that signal fraud at banks, retailers, and payment apps. Typical pay $70k.
Data Governance Analyst: Makes sure a company's data is accurate, well labeled and used according to the rules. Typical pay $95k.
Election Decision Desk Analyst: Crunches live vote counts on election night to decide when it is safe for a TV network or news service to declare a winner. Typical pay $95k.
Starter: fastest way in
Statistical Assistant: Helps statisticians and researchers by collecting, organizing, and checking data. Typical pay $52k.
Data Entry Keyer: Types and updates information in computer systems from forms, documents, and records. Typical pay $39k.
Sports Data Stringer: Watches games live and logs every play into a system that feeds sports apps, broadcasters, and betting companies. Typical pay $25k.
Data Operations Associate: Keeps data flowing correctly by checking uploads, fixing errors and cleaning up records. Typical pay $48k.
Career Universe is an early version. Pay, training and AI-risk figures are estimates to start your own research, not verified facts. The research was written with AI research assistants, checked by validation scripts and spot-checked by hand. Check anything important with schools, employers and official sources. How the numbers work.