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Career Profile: Data Science in Industry

The data science in industry career at a glance

Education: MS or PhD in physics or other scientific or computational field or a BS with relevant skills and experience can be sufficient

Additional training: Experience in programming, machine learning, or working with databases

Salary: Starting at $80K - $100K, with mid-career salaries at $160K - $180K

Outlook: The private sector employs over half of physics PhDs and about 95% of those with a bachelors in physics. Specifically, data science is a growing field with many job opportunities for physics degree holders.

What they do

A physicist in a data science job will spend most of their time analyzing data and designing and developing models to predict how something will behave based on data of how it has behaved in the past. Data scientists often work with a team to complete projects. Typical activities include:

  • Design, develop, and maintain machine learning and other data models
  • Select, use, and debug existing data models
  • Perform statistical and data analyses, often to make decisions about products or projected audiences
  • Conduct research to learn more about the field and to improve model accuracy, including meeting with and interviewing experts
  • Work in teams to assess project needs and perform tasks

Some data scientists also work on:

  • Data visualization, e.g. using Jupyter Notebooks/Python
  • Database management and data quality monitoring
  • Data infrastructure systems, which consist of all tools and software needed to collect, store, and analyze datasets
  • Web development
  • Communication with multiple teams, such as marketing, technical, etc.

Education & background

A bachelors in physics or other scientific/computational field can be sufficient, but a masters or PhD in these fields is often preferred. Programming skills and familiarity with machine learning, databases, and statistics are critical.

Commonly used languages in data science include: Python, R, SQL, SAS, and Scala. Having some knowledge or experience with one or more of these can make candidates more attractive for data science jobs.

Unlike many academic positions, experience in postdoctoral appointments is not considered a prerequisite for data science jobs in most private sector companies.

Additional training

Technical experience in the following can better prepare candidates for data science jobs and increase chances of hire:

  • Machine learning projects (like participating in a competition like Kaggle.com, an online machine learning resource hosted by Google)
  • Python, R, or Scala programming language
  • SQL experience with large databases
  • Web development projects
  • Internship in data science or related field

Resources to help build these skills include Coursera courses for gaining knowledge, LeetCode for practicing skills, and Kaggle. The book Cracking the Coding Interview can be a helpful guide when preparing for job interviews. 

Effective communication and collaboration skills can also set candidates apart. Students and early career physicists often have translatable skills, such as experience working in scientific collaborations or giving talks at conferences. Additionally, to succeed in industry, one has to be flexible in changing projects and willing to learn new skills. A defining characteristic of jobs in industry is that things move quickly; being able to work efficiently on projects and meet deadlines is key.

When applying for a job in the private sector, understanding the difference between a CV and a resume and being able to write a good resume are very important. For a good tutorial on the difference between CVs and resumes, and for advice on how to write a skills based resume suitable for private sector jobs, please watch our video tutorial.

Career path

Most physicists will start out as a data scientist or analyst, spending a majority of their time writing/developing code. After working for about 5 years or so as an individual contributor, some will move into more senior positions, choosing either leadership roles or continuing to be an individual contributor as a senior data scientist. Other options include being a technical leader or architect, or a manager. In such a role, a data scientist would spend most of their time on project, resource and personnel management. High level management positions in companies carry among the highest salaries for physicists in the private sector.


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