Thinking about diving into a career in data but are torn between Statistics and Data Science? You’re not alone—both fields are super popular and offer exciting opportunities, but they have some key differences in skills and job roles. In this blog, we’ll break down what each path involves to help you figure out which one might be your perfect fit!

Before we look at the job opportunities it’s important to know what skills are needed for each path and see which one you’re better qualified for.

Category | Data Science Skills | Statistics Skills |
---|---|---|

Programming | Python, R, SQL | Basic programming (mainly R), focused on statistical software |

Mathematical Foundations | Basic math, probability, and linear algebra | Strong foundation in calculus, probability, and linear algebra |

Statistical Analysis | Applied in machine learning models | Core skill, including hypothesis testing and inference |

Machine Learning & AI | Key focus area, involving algorithms for automation | Not typically a focus |

Big Data Tools | Hadoop, Spark, NoSQL databases | Rarely used |

Data Engineering | ETL processes, data warehousing, and cloud technologies | Not emphasized |

Data Collection | Not a core focus, but used in building datasets | Strong focus on experimental design and data collection |

Predictive Modeling | Built through machine learning algorithms | Core skill using statistical models |

Statistics focuses on theoretical methods and statistical rigor, while Data Science emphasizes practical application, coding, and machine learning to solve complex, real-world problems.

Both fields have many career opportunities, but data science has more due to the broad application of machine learning and big data across various industries. If you are not sure about where to start, check out these Data Science Job boards.

Data Science is a broader field and includes programming, machine learning, and big data tools. It has a rapidly expanding job market because businesses are applying machine learning and big data techniques to make smart decisions. They are in demand in industries such as finance, marketing, healthcare, tech, and e-commerce.

The job market for Statistics is growing. They have opportunities in different industries such as healthcare, government, and insurance. Statisticians are in demand because they can design experiments, analyze data, and draw conclusions for smart business decisions. Job roles such as biostatisticians, survey statisticians, Research Scientists, Data analysts, and risk analysts are common.

Both of these fields have a lot of career growth, but as you’ll read one industry is more profitable than the other. If you’re looking to switch industries or get a leg up in the recruiting process, a Masters degree is right for you.

As of 2024, the average salary for data scientists is $122,738 per year which equals to 59 dollars an hour. Most data scientists earn between 98,500 - 136,000 dollars a year, but the highest-paid can make up to 196,500 dollars. Entry-level salaries can start as low as 37,500. People in the top 10% of the field earn around 173,000 annually.

How much a data scientist makes really depends on their experience and where they work. Senior-level data scientists usually pull in more cash, and if you're in a big city or tech hub like San Francisco or New York, expect even higher pay. That’s because the cost of living is higher, and the demand for these skills is super high too.

As of 2024, the average salary for a statistician in the U.S. is $86,921 per year, which comes out to about 41.79 dollars an hour. Most statisticians make between 57,500 - 98,500 dollars a year, but salaries can go as high as 116,500 dollars. The top 10% of statisticians are earning around 116,000.

Your paycheck as a statistician depends on where you're working and what your role is. Bigger cities or more specialized positions usually pay more!

If you are choosing between data science and statistics, it depends on your interests, what your career goals are, and what you enjoy. If you enjoy working with pure math, theory, and research-based problems then statistics is the career path for you. If you want to mix programming with statistics and solve more practical and business-related problems then data science is the right path for you. Data science has more career opportunities and usually pays more but it also requires more diverse skills. Statistics is a great career if you enjoy focusing on research or analytics and love the mathematical side of things.

If Data Science is calling your name, here are 5 top online Data Science certificates and bootcamps to kickstart your journey, plus some resources to learn SQL (a must-have skill).

DataLemur offers tons of practice questions in ML, Statistics, SQL, and Python, along with interview guides for hundreds of companies to get you job-ready.

Here's an awesome SQL tutorial to get started: