What does a senior data scientist do?

A senior data scientist is responsible for using data to provide business solutions that shape enterprise strategies and product development. In addition to standard data analysis work, senior data scientists also play a key role in the development of machine learning models, defining the business problem and the resources needed to solve it to junior data scientists who will then perform exploratory data analysis and build the machine learning model. 

How do you become a senior data scientist?

• Senior data scientists are key players within a business and require extensive education and experience. 

In an increasing number of industries, senior data scientists play a critical role in developing business strategies and directing growth. This role requires extensive knowledge of programming, algorithm use, analysis and machine learning, so a strong educational background and years of experience in a data-facing analytics role will be necessary for qualified candidates. A bachelor’s degree in data science, computer science or mathematics is the baseline requirement for most senior data scientist roles; however, many may also require a master’s degree in data science, machine learning or business intelligence to be qualified.

The most natural path to becoming a senior data scientist is by having years of experience working as a data scientist. This will provide the necessary knowledge for succeeding in this role, particularly when it comes to building and executing machine learning models. Previous experience as a senior data analyst or senior business analyst will also provide the foundational data and business knowledge needed to accurately define business problems and the resources needed to find a solution.

What skills does a senior data scientist need?

• Senior data scientists need an expert-level understanding of machine learning, as well as superb data analysis skills.

Senior data scientists are typically responsible for both drawing informed solutions from machine learning models and performing high-priority data analysis work. Accordingly, the ability to know how to find the data needed, mine data, store data, analyze data and manage data at an expert level is a top qualification for the role. Strong machine learning capabilities are equally as important, including knowing how to collect and analyze data for the model, build the model, input data and analyze results from the model. Most importantly, senior data scientists must have the business acumen to properly define the business problem the machine learning model must provide predictions for, including the resources and workflows junior data scientists will need to use to efficiently execute the model. 

The senior data scientist also develops the dataset that will be used for the model, so having programming skills in Python and R will be necessary. Finally, senior data scientists must also have strong management and communication skills for ensuring their team is capable of delivering machine learning predictions that the senior data scientist will then explain to stakeholders in an easy-to-understand manner.

What is the salary of a senior data scientist?

• The average base salary of a senior data scientist in the United States is $143,138.

Due to the critical nature of the senior data scientist position, professionals in this role often receive the highest salaries in an organization’s data science department. In the United States, senior data scientists make an average base salary of $143,138, according to Built In. Senior data scientists also make an average of $18,513 in additional cash compensation, bringing the average total salary of a U.S.-based senior data scientist to $161,651. Built In collects senior data scientist salary data from responses submitted by anonymous senior data scientists in the U.S., with salary data updated in real time.