Adjacent degree route

How to Become a Data Scientist

For a space studies graduate, how to become a data scientist is a skills question more than a domain question. Mathematics, statistics, computer science, or a related field is the normal degree route. Astronomy and engineering can be adjacent when your transcript and portfolio show serious statistics, programming, algorithms, and data work. This guide explains how to become a data scientist from education through entry-level work.

Editorial illustration of a data scientist examining mission telemetry patterns at a workstation.
RouteAdjacentThe degree can transfer, but you must add targeted preparation.
Typical entry educationBachelor's degreeBLS Occupational Outlook Handbook
National median$120,230May 2025 BLS OEWS
National wage range$67,240–$199,13010th to 90th percentile

The occupation

What does a data scientist do?

Data scientists identify useful data, collect and organize it, create and test models, use algorithms and statistical methods, visualize findings, and explain what an organization should do with the result.

Use these duties as the first reality check when planning how to become a data scientist.

  • Identify and collect data relevant to a problem
  • Clean, categorize, and analyze datasets
  • Create, validate, and update algorithms and models
  • Use visualization to communicate findings
  • Make recommendations based on the analysis

The working day

A day in the life of a data scientist

A day often starts before the model. You clarify the decision that needs support, inspect the available data, and decide whether the data actually represents the question being asked.

Then you clean, analyze, and model. The last step is not a chart for its own sake. You explain the result, its uncertainty, and what action the evidence supports to people who may not share your technical background.

Education route

How to Become a Data Scientist, Step by Step

When you plan how to become a data scientist, use the sequence below to see where a space-focused degree fits and where you need additional preparation. A quantitative space science or engineering degree can transfer when it includes statistics, programming, algorithms, and a strong applied data portfolio.

  1. 01

    Build the mathematical base

    Statistics, probability, linear algebra, and calculus help you understand what a model can and cannot claim.

  2. 02

    Learn programming and data systems

    You need to manipulate data, implement models, test code, and work with the systems that store and deliver information.

  3. 03

    Turn space projects into decision evidence

    A scientific project helps when you can show the question, data preparation, method, validation, result, and limitations.

  4. 04

    Create an applied portfolio

    Use more than polished visualizations. Include reproducible analysis, documented code, model evaluation, and a plain-language explanation.

  5. 05

    Aim for roles that value your domain

    Scientific research, engineering, satellite, remote-sensing, and operations organizations may value both quantitative skill and familiarity with technical data.

Where the work happens

Where data scientists work

Office and computing environments

Data scientists spend much of their time working with code, models, data systems, documentation, and teams.

Research organizations

Scientific R&D settings use data scientists to support experiments, instrumentation, simulations, and technical decisions.

Organizations across the economy

Computer services, insurance, management organizations, consulting, and many other sectors employ data scientists.

Technical directions

Data Scientist specialties and focus areas

Statistical modeling

This work focuses on estimation, uncertainty, relationships, and whether a result holds beyond the sample.

Machine learning

Machine-learning work develops and evaluates algorithms that detect patterns or make predictions.

Scientific data

Scientific roles work with sensor, experiment, observation, and simulation data where the measurement process matters.

Data communication

Visualization and explanation help technical and nontechnical decision makers understand the result and its limits.

Before you commit

The hard parts of becoming a data scientist

Your major name will not prove the skill set

Astronomy and engineering can be quantitative, but you still need visible evidence of statistics, programming, model evaluation, and data systems.

Most of the work happens before the polished model

Collecting, cleaning, defining, and checking data often determine whether the result is useful.

A technically strong answer can still be unusable

You must explain findings and limitations to people who make decisions without hiding behind mathematical language.

Some employers want graduate depth

BLS lists a bachelor’s degree as typical, but notes that some jobs require or prefer a master’s or doctoral degree.

BLS wage data

How much do data scientists make?

The national median is $120,230. The full OEWS wage span runs from $67,240 at the 10th percentile to $199,130 at the 90th. A percentile is a place in the wage distribution, not a promise about your experience level.

See data scientist salary by state

Common questions

How to Become a Data Scientist: common questions

Can a space studies degree lead to data science?
What degree do data scientists need?
Is astronomy good preparation for data science?
What should a data science portfolio show?
Where do data scientists work?

Primary sources

Sources for how to become a data scientist

Occupation facts and wage records reviewed August 28, 2026.