What Is a Data Science Manager?

Data science positions have grown to be some of the most high-demand jobs in recent years. An increase in the amount of data companies have access to presents an opportunity to leverage this data and draw valuable insights, allowing businesses to make better, more informed decisions and predictions. As such, data science positions feature a strong outlook that is well above the national average.

Data science managers are extremely valuable and are applicable in virtually every industry, offering plenty of opportunities for individuals willing to learn the skills and strive to advance to managerial positions in their careers.

What is a data science manager?

A data science manager is an individual responsible for managing a team of data scientists. You'll typically reach this position after having years of experience working directly with data, as a data scientist, or in a similarly related position, such as a data analyst. As a manager, however, you are responsible for identifying and setting goals for your team. This means a data science manager will need strong leadership, communication, and project management skills in addition to your knowledge of data structures, analysis, and other technical concepts to be able to properly implement your strategies. You will be in regular communication with those in leadership positions to effectively identify what insights need to be found.

What does a data science manager do?

While having strong technical skills is going to be a requirement for obtaining a data science manager position, most of your time will be spent managing and organizing the strategy and development of your team. Your team members will do the majority of the direct work with data under your guidance. To provide direction and assistance, however, you must have the necessary data science abilities to help your team complete a given task. 

Data science manager tasks and responsibilities 

One important task you will have as a data science manager is building the best possible team. This means identifying the right people to add value to your data science team based on each individual's unique strengths, listening and acting on feedback, and addressing any skills gaps. 

To do this well, you should have clearly defined goals for your projects, making it crucial for you to understand the needs of shareholders and other members of your business. Your responsibilities as a data science manager ultimately include the following:

• Managing data science team members

• Identifying objectives and goals

• Developing processes for your team to obtain given objectives

• Supporting data-driven decisions

• Building relationships with team members

• Measuring the direct impact of your team

What tools do data science managers use?

Data scientists need to have working knowledge of a wide variety of data science tools. Since this job is multi-dimensional, understanding tools related to data visualization, data processing, statistical analysis, data analysis, and machine learning are all important for you to contribute to the success of a data science team. A data science manager should be familiar with each to use them effectively. Here’s a list of data science tools and their applications:

• Data visualization: Tableau, Matplotlib, ggplot, D3.js

• Data processing: Apache spark, Apache Hadoop,Matlab

• Statistical analysis: SAS, R

• Data analysis: Python, Jupyter Notebook, SQL

• Machine learning: scikit-learn, TensorFlow

Data science manager salary and job outlook

According to Glassdoor, the average data science manager base salary is $161,963, with an average additional bonus of $77,526, equating to an average income of $239,489 [1]. The industries paying the highest salaries for data science managers are information technology and financial services. 

Data science positions also feature a strong job outlook, with the US Bureau of Labor Statistics projecting significant growth at 35 percent for data scientists from 2022 to 2032 [2]. California employs the most data scientists, followed by Texas, New York, Florida, and Pennsylvania. 

How to become a data science manager

Progressing to the level of a data science manager comes with certain education, skill, and career experience expectations. The exact requirements will vary from company to company as some may value technical expertise more heavily while others are more concerned with management experience. This section will cover various standards expected by employers, so you can put yourself in a position to become a data science manager. 

Education

Becoming a data science manager will typically start with a bachelor’s degree but to progress to manager, you’ll likely need a master’s degree. When it comes to the major of your degree, however, you have some options. Degrees in computer science, information systems, mathematics, statistics, or data analytics are common and acceptable in addition to data science degrees. 

Training

To reach a managerial position, additional training options are available to boost your qualifications. Options for data science management jobs include Certified Analytics Professional programs. These certifications require passing exams. Obtaining a certification can help you gain a better understanding of management positions and develop your critical decision-making skills.

Experience

Making a move to become a data science manager will generally require several years of experience as a data scientist or a similar role in addition to one to three years of experience in a supervisory or leadership position. The ability to think strategically, beyond executing technical tasks and responsibilities, is an important characteristic for data science managers, and you can develop this skill through experience working in senior-level positions.

Skills

Your success as a data science manager requires both technical skills and leadership skills. Technical skills needed are analytical skills, computer skills such as coding, an understanding of data analytics and visualization tools, and math skills including statistics and linear algebra. To effectively manage a team, you need excellent leadership skills. This will allow you to help team members develop their abilities, foster a positive work environment and prioritize tasks. 

Data science manager career advancement

While reaching the level of data science manager is a great career achievement, you can take your career even further and strive to obtain other data science-related positions. For example, other positions you could potentially transition to include machine learning engineer or enterprise architect.

Get started today

Data science is an in-demand field, with data science manager positions commanding high salaries and excellent job outlooks for those who have built up relevant experience and earned a master’s degree. On Coursera, you can find a variety of data science courses and programs to further develop your skill set and bring you one step closer to becoming a data science manager. 

Those new to data science can progress towards their career by earning an IBM Data Science Professional Certificate. In this program, you can develop job-ready tools and skills, including Python, SQL, and data visualization. 

You can also find more advanced-level data science courses on Coursera, such as Data Science Foundations: Data Structures and Algorithms Specializations from the University of Colorado Boulder. In this course, you'll learn to solve data structure problems by designing and analyzing algorithms for different applications.